Analysis of 111/999 NHS calls and 111 online reports
Quentin Leclerc, Emily Nightingale, Samuel Abbott & Thibaut Jombart, for CMMID
Sunday 21 February 2021
1 Data preparation
1.1 Outline
Load scripts: loads libraries and useful scripts used in the analyses; all
.Rfiles contained inscriptsat the root of the factory are automatically loadedLoad data: imports datasets, and may contain some ad hoc changes to the data such as specific data cleaning (not used in other reports), new variables used in the analyses, etc.
1.2 Load packages
library(reportfactory)
library(here)
library(rio)
library(tidyverse)
library(incidence)
library(distcrete)
library(epitrix)
library(earlyR)
library(projections)
library(linelist)
library(remotes)
library(janitor)
library(kableExtra)
library(DT)
library(cyphr)
library(chngpt)
library(lubridate)
library(ggpubr)
library(ggnewscale)1.3 Load scripts
These scripts will load:
- all scripts stored as
.Rfiles inside/scripts/ - all scripts stored as
.Rfiles inside/src/
These scripts also contain routines to access the latest clean encrypted data (see next section).
1.4 Load clean data
We import the latest NHS pathways data:
x <- import_pathways() %>%
as_tibble()
x
## [90m# A tibble: 442,730 x 11[39m
## site_type date sex age ccg_code ccg_name count postcode nhs_region
## [3m[90m<chr>[39m[23m [3m[90m<date>[39m[23m [3m[90m<chr>[39m[23m [3m[90m<chr>[39m[23m [3m[90m<chr>[39m[23m [3m[90m<chr>[39m[23m [3m[90m<int>[39m[23m [3m[90m<chr>[39m[23m [3m[90m<chr>[39m[23m
## [90m 1[39m 111 2020-03-18 fema… miss… e380000… nhs_glo… 1 gl34fe South West
## [90m 2[39m 111 2020-03-18 fema… miss… e380001… nhs_sou… 1 ne325nn North Eas…
## [90m 3[39m 111 2020-03-18 fema… 0-18 e380000… nhs_air… 8 bd57jr North Eas…
## [90m 4[39m 111 2020-03-18 fema… 0-18 e380000… nhs_ash… 7 tn254ab South East
## [90m 5[39m 111 2020-03-18 fema… 0-18 e380000… nhs_bar… 35 rm13ae London
## [90m 6[39m 111 2020-03-18 fema… 0-18 e380000… nhs_bar… 9 n111np London
## [90m 7[39m 111 2020-03-18 fema… 0-18 e380000… nhs_bar… 11 s752py North Eas…
## [90m 8[39m 111 2020-03-18 fema… 0-18 e380000… nhs_bas… 19 ss143hg East of E…
## [90m 9[39m 111 2020-03-18 fema… 0-18 e380000… nhs_bas… 6 dn227xf North Eas…
## [90m10[39m 111 2020-03-18 fema… 0-18 e380000… nhs_bat… 9 ba25rp South West
## [90m# … with 442,720 more rows, and 2 more variables: day [3m[90m<int>[90m[23m, weekday [3m[90m<fct>[90m[23m[39mWe also import demographics data for NHS regions in England, used later in our analysis:
path <- here::here("data", "csv", "nhs_region_population_2018.csv")
nhs_region_pop <- rio::import(path) %>%
mutate(nhs_region = str_to_title(gsub("_"," ",nhs_region)))
nhs_region_pop$nhs_region <- gsub(" Of ", " of ", nhs_region_pop$nhs_region)
nhs_region_pop$nhs_region <- gsub(" And ", " and ", nhs_region_pop$nhs_region)
nhs_region_pop
## nhs_region variable value
## 1 North West 0-18 0.22538599
## 2 North East and Yorkshire 0-18 0.21876449
## 3 Midlands 0-18 0.22564656
## 4 East of England 0-18 0.22810783
## 5 London 0-18 0.23764782
## 6 South East 0-18 0.22458811
## 7 South West 0-18 0.20799797
## 8 North West 19-69 0.64274078
## 9 North East and Yorkshire 19-69 0.64437753
## 10 Midlands 19-69 0.63876675
## 11 East of England 19-69 0.63034229
## 12 London 19-69 0.67820084
## 13 South East 19-69 0.63267336
## 14 South West 19-69 0.63176131
## 15 North West 70-120 0.13187323
## 16 North East and Yorkshire 70-120 0.13685797
## 17 Midlands 70-120 0.13558669
## 18 East of England 70-120 0.14154988
## 19 London 70-120 0.08415135
## 20 South East 70-120 0.14273853
## 21 South West 70-120 0.16024072Finally, we import publically available deaths per NHS region:
dth <- import_deaths() %>%
mutate(nhs_region = str_to_title(gsub("_"," ",nhs_region)))
#truncation to account for reporting delay
delay_max <- 21
dth$nhs_region <- gsub(" Of ", " of ", dth$nhs_region)
dth$nhs_region <- gsub(" And ", " and ", dth$nhs_region)
dth
## date_report nhs_region deaths
## 1 2020-03-01 East of England 0
## 2 2020-03-02 East of England 1
## 3 2020-03-03 East of England 0
## 4 2020-03-04 East of England 0
## 5 2020-03-05 East of England 0
## 6 2020-03-06 East of England 1
## 7 2020-03-07 East of England 0
## 8 2020-03-08 East of England 0
## 9 2020-03-09 East of England 1
## 10 2020-03-10 East of England 0
## 11 2020-03-11 East of England 0
## 12 2020-03-12 East of England 0
## 13 2020-03-13 East of England 1
## 14 2020-03-14 East of England 2
## 15 2020-03-15 East of England 2
## 16 2020-03-16 East of England 1
## 17 2020-03-17 East of England 1
## 18 2020-03-18 East of England 5
## 19 2020-03-19 East of England 4
## 20 2020-03-20 East of England 2
## 21 2020-03-21 East of England 11
## 22 2020-03-22 East of England 12
## 23 2020-03-23 East of England 11
## 24 2020-03-24 East of England 19
## 25 2020-03-25 East of England 26
## 26 2020-03-26 East of England 36
## 27 2020-03-27 East of England 38
## 28 2020-03-28 East of England 28
## 29 2020-03-29 East of England 43
## 30 2020-03-30 East of England 45
## 31 2020-03-31 East of England 70
## 32 2020-04-01 East of England 63
## 33 2020-04-02 East of England 65
## 34 2020-04-03 East of England 80
## 35 2020-04-04 East of England 71
## 36 2020-04-05 East of England 76
## 37 2020-04-06 East of England 71
## 38 2020-04-07 East of England 93
## 39 2020-04-08 East of England 111
## 40 2020-04-09 East of England 87
## 41 2020-04-10 East of England 74
## 42 2020-04-11 East of England 92
## 43 2020-04-12 East of England 100
## 44 2020-04-13 East of England 78
## 45 2020-04-14 East of England 61
## 46 2020-04-15 East of England 82
## 47 2020-04-16 East of England 74
## 48 2020-04-17 East of England 86
## 49 2020-04-18 East of England 64
## 50 2020-04-19 East of England 67
## 51 2020-04-20 East of England 67
## 52 2020-04-21 East of England 75
## 53 2020-04-22 East of England 67
## 54 2020-04-23 East of England 49
## 55 2020-04-24 East of England 66
## 56 2020-04-25 East of England 54
## 57 2020-04-26 East of England 48
## 58 2020-04-27 East of England 46
## 59 2020-04-28 East of England 58
## 60 2020-04-29 East of England 32
## 61 2020-04-30 East of England 45
## 62 2020-05-01 East of England 49
## 63 2020-05-02 East of England 29
## 64 2020-05-03 East of England 41
## 65 2020-05-04 East of England 19
## 66 2020-05-05 East of England 36
## 67 2020-05-06 East of England 31
## 68 2020-05-07 East of England 33
## 69 2020-05-08 East of England 33
## 70 2020-05-09 East of England 29
## 71 2020-05-10 East of England 22
## 72 2020-05-11 East of England 18
## 73 2020-05-12 East of England 21
## 74 2020-05-13 East of England 27
## 75 2020-05-14 East of England 26
## 76 2020-05-15 East of England 19
## 77 2020-05-16 East of England 26
## 78 2020-05-17 East of England 17
## 79 2020-05-18 East of England 25
## 80 2020-05-19 East of England 15
## 81 2020-05-20 East of England 26
## 82 2020-05-21 East of England 21
## 83 2020-05-22 East of England 13
## 84 2020-05-23 East of England 12
## 85 2020-05-24 East of England 17
## 86 2020-05-25 East of England 25
## 87 2020-05-26 East of England 14
## 88 2020-05-27 East of England 12
## 89 2020-05-28 East of England 17
## 90 2020-05-29 East of England 16
## 91 2020-05-30 East of England 9
## 92 2020-05-31 East of England 8
## 93 2020-06-01 East of England 17
## 94 2020-06-02 East of England 14
## 95 2020-06-03 East of England 10
## 96 2020-06-04 East of England 7
## 97 2020-06-05 East of England 14
## 98 2020-06-06 East of England 5
## 99 2020-06-07 East of England 9
## 100 2020-06-08 East of England 7
## 101 2020-06-09 East of England 6
## 102 2020-06-10 East of England 8
## 103 2020-06-11 East of England 1
## 104 2020-06-12 East of England 9
## 105 2020-06-13 East of England 5
## 106 2020-06-14 East of England 4
## 107 2020-06-15 East of England 8
## 108 2020-06-16 East of England 3
## 109 2020-06-17 East of England 7
## 110 2020-06-18 East of England 4
## 111 2020-06-19 East of England 7
## 112 2020-06-20 East of England 4
## 113 2020-06-21 East of England 3
## 114 2020-06-22 East of England 6
## 115 2020-06-23 East of England 5
## 116 2020-06-24 East of England 4
## 117 2020-06-25 East of England 1
## 118 2020-06-26 East of England 5
## 119 2020-06-27 East of England 6
## 120 2020-06-28 East of England 8
## 121 2020-06-29 East of England 4
## 122 2020-06-30 East of England 5
## 123 2020-07-01 East of England 2
## 124 2020-07-02 East of England 5
## 125 2020-07-03 East of England 0
## 126 2020-07-04 East of England 3
## 127 2020-07-05 East of England 1
## 128 2020-07-06 East of England 2
## 129 2020-07-07 East of England 2
## 130 2020-07-08 East of England 0
## 131 2020-07-09 East of England 8
## 132 2020-07-10 East of England 4
## 133 2020-07-11 East of England 2
## 134 2020-07-12 East of England 1
## 135 2020-07-13 East of England 8
## 136 2020-07-14 East of England 2
## 137 2020-07-15 East of England 0
## 138 2020-07-16 East of England 0
## 139 2020-07-17 East of England 0
## 140 2020-07-18 East of England 0
## 141 2020-07-19 East of England 1
## 142 2020-07-20 East of England 1
## 143 2020-07-21 East of England 1
## 144 2020-07-22 East of England 2
## 145 2020-07-23 East of England 1
## 146 2020-07-24 East of England 1
## 147 2020-07-25 East of England 0
## 148 2020-07-26 East of England 1
## 149 2020-07-27 East of England 1
## 150 2020-07-28 East of England 2
## 151 2020-07-29 East of England 0
## 152 2020-07-30 East of England 0
## 153 2020-07-31 East of England 1
## 154 2020-08-01 East of England 0
## 155 2020-08-02 East of England 0
## 156 2020-08-03 East of England 0
## 157 2020-08-04 East of England 1
## 158 2020-08-05 East of England 1
## 159 2020-08-06 East of England 0
## 160 2020-08-07 East of England 1
## 161 2020-08-08 East of England 0
## 162 2020-08-09 East of England 0
## 163 2020-08-10 East of England 1
## 164 2020-08-11 East of England 2
## 165 2020-08-12 East of England 1
## 166 2020-08-13 East of England 0
## 167 2020-08-14 East of England 1
## 168 2020-08-15 East of England 1
## 169 2020-08-16 East of England 0
## 170 2020-08-17 East of England 0
## 171 2020-08-18 East of England 2
## 172 2020-08-19 East of England 1
## 173 2020-08-20 East of England 1
## 174 2020-08-21 East of England 0
## 175 2020-08-22 East of England 1
## 176 2020-08-23 East of England 1
## 177 2020-08-24 East of England 0
## 178 2020-08-25 East of England 0
## 179 2020-08-26 East of England 1
## 180 2020-08-27 East of England 1
## 181 2020-08-28 East of England 0
## 182 2020-08-29 East of England 0
## 183 2020-08-30 East of England 0
## 184 2020-08-31 East of England 0
## 185 2020-09-01 East of England 0
## 186 2020-09-02 East of England 0
## 187 2020-09-03 East of England 1
## 188 2020-09-04 East of England 1
## 189 2020-09-05 East of England 0
## 190 2020-09-06 East of England 1
## 191 2020-09-07 East of England 0
## 192 2020-09-08 East of England 0
## 193 2020-09-09 East of England 0
## 194 2020-09-10 East of England 0
## 195 2020-09-11 East of England 0
## 196 2020-09-12 East of England 0
## 197 2020-09-13 East of England 1
## 198 2020-09-14 East of England 1
## 199 2020-09-15 East of England 0
## 200 2020-09-16 East of England 0
## 201 2020-09-17 East of England 0
## 202 2020-09-18 East of England 0
## 203 2020-09-19 East of England 0
## 204 2020-09-20 East of England 2
## 205 2020-09-21 East of England 0
## 206 2020-09-22 East of England 2
## 207 2020-09-23 East of England 1
## 208 2020-09-24 East of England 0
## 209 2020-09-25 East of England 1
## 210 2020-09-26 East of England 1
## 211 2020-09-27 East of England 1
## 212 2020-09-28 East of England 2
## 213 2020-09-29 East of England 2
## 214 2020-09-30 East of England 2
## 215 2020-10-01 East of England 2
## 216 2020-10-02 East of England 1
## 217 2020-10-03 East of England 1
## 218 2020-10-04 East of England 0
## 219 2020-10-05 East of England 0
## 220 2020-10-06 East of England 4
## 221 2020-10-07 East of England 6
## 222 2020-10-08 East of England 3
## 223 2020-10-09 East of England 1
## 224 2020-10-10 East of England 6
## 225 2020-10-11 East of England 2
## 226 2020-10-12 East of England 2
## 227 2020-10-13 East of England 1
## 228 2020-10-14 East of England 3
## 229 2020-10-15 East of England 4
## 230 2020-10-16 East of England 5
## 231 2020-10-17 East of England 6
## 232 2020-10-18 East of England 7
## 233 2020-10-19 East of England 5
## 234 2020-10-20 East of England 9
## 235 2020-10-21 East of England 7
## 236 2020-10-22 East of England 7
## 237 2020-10-23 East of England 14
## 238 2020-10-24 East of England 1
## 239 2020-10-25 East of England 10
## 240 2020-10-26 East of England 10
## 241 2020-10-27 East of England 8
## 242 2020-10-28 East of England 12
## 243 2020-10-29 East of England 10
## 244 2020-10-30 East of England 12
## 245 2020-10-31 East of England 15
## 246 2020-11-01 East of England 14
## 247 2020-11-02 East of England 9
## 248 2020-11-03 East of England 14
## 249 2020-11-04 East of England 11
## 250 2020-11-05 East of England 12
## 251 2020-11-06 East of England 18
## 252 2020-11-07 East of England 10
## 253 2020-11-08 East of England 13
## 254 2020-11-09 East of England 16
## 255 2020-11-10 East of England 26
## 256 2020-11-11 East of England 14
## 257 2020-11-12 East of England 14
## 258 2020-11-13 East of England 21
## 259 2020-11-14 East of England 19
## 260 2020-11-15 East of England 13
## 261 2020-11-16 East of England 11
## 262 2020-11-17 East of England 17
## 263 2020-11-18 East of England 19
## 264 2020-11-19 East of England 23
## 265 2020-11-20 East of England 24
## 266 2020-11-21 East of England 19
## 267 2020-11-22 East of England 21
## 268 2020-11-23 East of England 18
## 269 2020-11-24 East of England 21
## 270 2020-11-25 East of England 19
## 271 2020-11-26 East of England 19
## 272 2020-11-27 East of England 14
## 273 2020-11-28 East of England 28
## 274 2020-11-29 East of England 19
## 275 2020-11-30 East of England 22
## 276 2020-12-01 East of England 26
## 277 2020-12-02 East of England 18
## 278 2020-12-03 East of England 24
## 279 2020-12-04 East of England 25
## 280 2020-12-05 East of England 25
## 281 2020-12-06 East of England 21
## 282 2020-12-07 East of England 16
## 283 2020-12-08 East of England 26
## 284 2020-12-09 East of England 19
## 285 2020-12-10 East of England 32
## 286 2020-12-11 East of England 32
## 287 2020-12-12 East of England 27
## 288 2020-12-13 East of England 25
## 289 2020-12-14 East of England 32
## 290 2020-12-15 East of England 35
## 291 2020-12-16 East of England 29
## 292 2020-12-17 East of England 42
## 293 2020-12-18 East of England 44
## 294 2020-12-19 East of England 54
## 295 2020-12-20 East of England 52
## 296 2020-12-21 East of England 66
## 297 2020-12-22 East of England 52
## 298 2020-12-23 East of England 61
## 299 2020-12-24 East of England 61
## 300 2020-12-25 East of England 58
## 301 2020-12-26 East of England 63
## 302 2020-12-27 East of England 54
## 303 2020-12-28 East of England 71
## 304 2020-12-29 East of England 53
## 305 2020-12-30 East of England 76
## 306 2020-12-31 East of England 82
## 307 2021-01-01 East of England 89
## 308 2021-01-02 East of England 66
## 309 2021-01-03 East of England 78
## 310 2021-01-04 East of England 87
## 311 2021-01-05 East of England 102
## 312 2021-01-06 East of England 99
## 313 2021-01-07 East of England 116
## 314 2021-01-08 East of England 95
## 315 2021-01-09 East of England 129
## 316 2021-01-10 East of England 123
## 317 2021-01-11 East of England 123
## 318 2021-01-12 East of England 128
## 319 2021-01-13 East of England 126
## 320 2021-01-14 East of England 125
## 321 2021-01-15 East of England 117
## 322 2021-01-16 East of England 128
## 323 2021-01-17 East of England 130
## 324 2021-01-18 East of England 119
## 325 2021-01-19 East of England 127
## 326 2021-01-20 East of England 147
## 327 2021-01-21 East of England 130
## 328 2021-01-22 East of England 118
## 329 2021-01-23 East of England 102
## 330 2021-01-24 East of England 100
## 331 2021-01-25 East of England 111
## 332 2021-01-26 East of England 86
## 333 2021-01-27 East of England 92
## 334 2021-01-28 East of England 109
## 335 2021-01-29 East of England 92
## 336 2021-01-30 East of England 82
## 337 2021-01-31 East of England 71
## 338 2021-02-01 East of England 61
## 339 2021-02-02 East of England 72
## 340 2021-02-03 East of England 80
## 341 2021-02-04 East of England 75
## 342 2021-02-05 East of England 65
## 343 2021-02-06 East of England 72
## 344 2021-02-07 East of England 61
## 345 2021-02-08 East of England 73
## 346 2021-02-09 East of England 62
## 347 2021-02-10 East of England 49
## 348 2021-02-11 East of England 52
## 349 2021-02-12 East of England 46
## 350 2021-02-13 East of England 44
## 351 2021-02-14 East of England 27
## 352 2021-02-15 East of England 41
## 353 2021-02-16 East of England 41
## 354 2021-02-17 East of England 42
## 355 2021-02-18 East of England 20
## 356 2021-02-19 East of England 4
## 357 2020-03-01 London 0
## 358 2020-03-02 London 0
## 359 2020-03-03 London 0
## 360 2020-03-04 London 0
## 361 2020-03-05 London 0
## 362 2020-03-06 London 1
## 363 2020-03-07 London 0
## 364 2020-03-08 London 0
## 365 2020-03-09 London 1
## 366 2020-03-10 London 0
## 367 2020-03-11 London 5
## 368 2020-03-12 London 6
## 369 2020-03-13 London 10
## 370 2020-03-14 London 13
## 371 2020-03-15 London 9
## 372 2020-03-16 London 15
## 373 2020-03-17 London 23
## 374 2020-03-18 London 28
## 375 2020-03-19 London 25
## 376 2020-03-20 London 44
## 377 2020-03-21 London 49
## 378 2020-03-22 London 54
## 379 2020-03-23 London 63
## 380 2020-03-24 London 86
## 381 2020-03-25 London 112
## 382 2020-03-26 London 130
## 383 2020-03-27 London 130
## 384 2020-03-28 London 123
## 385 2020-03-29 London 145
## 386 2020-03-30 London 151
## 387 2020-03-31 London 183
## 388 2020-04-01 London 202
## 389 2020-04-02 London 191
## 390 2020-04-03 London 199
## 391 2020-04-04 London 231
## 392 2020-04-05 London 195
## 393 2020-04-06 London 198
## 394 2020-04-07 London 220
## 395 2020-04-08 London 239
## 396 2020-04-09 London 207
## 397 2020-04-10 London 171
## 398 2020-04-11 London 178
## 399 2020-04-12 London 159
## 400 2020-04-13 London 166
## 401 2020-04-14 London 143
## 402 2020-04-15 London 143
## 403 2020-04-16 London 140
## 404 2020-04-17 London 101
## 405 2020-04-18 London 101
## 406 2020-04-19 London 104
## 407 2020-04-20 London 96
## 408 2020-04-21 London 96
## 409 2020-04-22 London 109
## 410 2020-04-23 London 77
## 411 2020-04-24 London 71
## 412 2020-04-25 London 58
## 413 2020-04-26 London 53
## 414 2020-04-27 London 52
## 415 2020-04-28 London 44
## 416 2020-04-29 London 45
## 417 2020-04-30 London 40
## 418 2020-05-01 London 41
## 419 2020-05-02 London 41
## 420 2020-05-03 London 36
## 421 2020-05-04 London 30
## 422 2020-05-05 London 25
## 423 2020-05-06 London 37
## 424 2020-05-07 London 37
## 425 2020-05-08 London 31
## 426 2020-05-09 London 23
## 427 2020-05-10 London 26
## 428 2020-05-11 London 18
## 429 2020-05-12 London 18
## 430 2020-05-13 London 17
## 431 2020-05-14 London 20
## 432 2020-05-15 London 19
## 433 2020-05-16 London 14
## 434 2020-05-17 London 16
## 435 2020-05-18 London 11
## 436 2020-05-19 London 14
## 437 2020-05-20 London 19
## 438 2020-05-21 London 12
## 439 2020-05-22 London 10
## 440 2020-05-23 London 6
## 441 2020-05-24 London 7
## 442 2020-05-25 London 9
## 443 2020-05-26 London 14
## 444 2020-05-27 London 7
## 445 2020-05-28 London 8
## 446 2020-05-29 London 7
## 447 2020-05-30 London 12
## 448 2020-05-31 London 6
## 449 2020-06-01 London 10
## 450 2020-06-02 London 8
## 451 2020-06-03 London 6
## 452 2020-06-04 London 8
## 453 2020-06-05 London 4
## 454 2020-06-06 London 0
## 455 2020-06-07 London 5
## 456 2020-06-08 London 5
## 457 2020-06-09 London 5
## 458 2020-06-10 London 8
## 459 2020-06-11 London 5
## 460 2020-06-12 London 3
## 461 2020-06-13 London 3
## 462 2020-06-14 London 3
## 463 2020-06-15 London 1
## 464 2020-06-16 London 2
## 465 2020-06-17 London 1
## 466 2020-06-18 London 2
## 467 2020-06-19 London 5
## 468 2020-06-20 London 3
## 469 2020-06-21 London 4
## 470 2020-06-22 London 2
## 471 2020-06-23 London 1
## 472 2020-06-24 London 4
## 473 2020-06-25 London 3
## 474 2020-06-26 London 2
## 475 2020-06-27 London 1
## 476 2020-06-28 London 2
## 477 2020-06-29 London 2
## 478 2020-06-30 London 1
## 479 2020-07-01 London 3
## 480 2020-07-02 London 2
## 481 2020-07-03 London 2
## 482 2020-07-04 London 1
## 483 2020-07-05 London 3
## 484 2020-07-06 London 2
## 485 2020-07-07 London 1
## 486 2020-07-08 London 3
## 487 2020-07-09 London 4
## 488 2020-07-10 London 0
## 489 2020-07-11 London 1
## 490 2020-07-12 London 1
## 491 2020-07-13 London 1
## 492 2020-07-14 London 0
## 493 2020-07-15 London 2
## 494 2020-07-16 London 0
## 495 2020-07-17 London 0
## 496 2020-07-18 London 2
## 497 2020-07-19 London 0
## 498 2020-07-20 London 0
## 499 2020-07-21 London 1
## 500 2020-07-22 London 0
## 501 2020-07-23 London 2
## 502 2020-07-24 London 0
## 503 2020-07-25 London 1
## 504 2020-07-26 London 0
## 505 2020-07-27 London 1
## 506 2020-07-28 London 0
## 507 2020-07-29 London 0
## 508 2020-07-30 London 1
## 509 2020-07-31 London 0
## 510 2020-08-01 London 0
## 511 2020-08-02 London 3
## 512 2020-08-03 London 0
## 513 2020-08-04 London 0
## 514 2020-08-05 London 0
## 515 2020-08-06 London 1
## 516 2020-08-07 London 0
## 517 2020-08-08 London 0
## 518 2020-08-09 London 0
## 519 2020-08-10 London 0
## 520 2020-08-11 London 1
## 521 2020-08-12 London 0
## 522 2020-08-13 London 2
## 523 2020-08-14 London 0
## 524 2020-08-15 London 0
## 525 2020-08-16 London 0
## 526 2020-08-17 London 1
## 527 2020-08-18 London 1
## 528 2020-08-19 London 0
## 529 2020-08-20 London 1
## 530 2020-08-21 London 0
## 531 2020-08-22 London 0
## 532 2020-08-23 London 0
## 533 2020-08-24 London 1
## 534 2020-08-25 London 1
## 535 2020-08-26 London 0
## 536 2020-08-27 London 0
## 537 2020-08-28 London 0
## 538 2020-08-29 London 0
## 539 2020-08-30 London 0
## 540 2020-08-31 London 1
## 541 2020-09-01 London 0
## 542 2020-09-02 London 1
## 543 2020-09-03 London 1
## 544 2020-09-04 London 0
## 545 2020-09-05 London 0
## 546 2020-09-06 London 2
## 547 2020-09-07 London 0
## 548 2020-09-08 London 0
## 549 2020-09-09 London 0
## 550 2020-09-10 London 2
## 551 2020-09-11 London 1
## 552 2020-09-12 London 1
## 553 2020-09-13 London 0
## 554 2020-09-14 London 0
## 555 2020-09-15 London 1
## 556 2020-09-16 London 2
## 557 2020-09-17 London 2
## 558 2020-09-18 London 1
## 559 2020-09-19 London 3
## 560 2020-09-20 London 3
## 561 2020-09-21 London 2
## 562 2020-09-22 London 6
## 563 2020-09-23 London 4
## 564 2020-09-24 London 3
## 565 2020-09-25 London 1
## 566 2020-09-26 London 1
## 567 2020-09-27 London 1
## 568 2020-09-28 London 3
## 569 2020-09-29 London 7
## 570 2020-09-30 London 6
## 571 2020-10-01 London 4
## 572 2020-10-02 London 1
## 573 2020-10-03 London 3
## 574 2020-10-04 London 2
## 575 2020-10-05 London 7
## 576 2020-10-06 London 4
## 577 2020-10-07 London 6
## 578 2020-10-08 London 6
## 579 2020-10-09 London 7
## 580 2020-10-10 London 3
## 581 2020-10-11 London 5
## 582 2020-10-12 London 7
## 583 2020-10-13 London 4
## 584 2020-10-14 London 6
## 585 2020-10-15 London 13
## 586 2020-10-16 London 6
## 587 2020-10-17 London 2
## 588 2020-10-18 London 5
## 589 2020-10-19 London 11
## 590 2020-10-20 London 8
## 591 2020-10-21 London 14
## 592 2020-10-22 London 12
## 593 2020-10-23 London 7
## 594 2020-10-24 London 18
## 595 2020-10-25 London 10
## 596 2020-10-26 London 10
## 597 2020-10-27 London 12
## 598 2020-10-28 London 23
## 599 2020-10-29 London 14
## 600 2020-10-30 London 17
## 601 2020-10-31 London 7
## 602 2020-11-01 London 17
## 603 2020-11-02 London 16
## 604 2020-11-03 London 10
## 605 2020-11-04 London 18
## 606 2020-11-05 London 17
## 607 2020-11-06 London 12
## 608 2020-11-07 London 21
## 609 2020-11-08 London 15
## 610 2020-11-09 London 28
## 611 2020-11-10 London 14
## 612 2020-11-11 London 15
## 613 2020-11-12 London 16
## 614 2020-11-13 London 14
## 615 2020-11-14 London 21
## 616 2020-11-15 London 18
## 617 2020-11-16 London 29
## 618 2020-11-17 London 29
## 619 2020-11-18 London 23
## 620 2020-11-19 London 24
## 621 2020-11-20 London 20
## 622 2020-11-21 London 19
## 623 2020-11-22 London 29
## 624 2020-11-23 London 19
## 625 2020-11-24 London 27
## 626 2020-11-25 London 30
## 627 2020-11-26 London 25
## 628 2020-11-27 London 28
## 629 2020-11-28 London 23
## 630 2020-11-29 London 40
## 631 2020-11-30 London 19
## 632 2020-12-01 London 28
## 633 2020-12-02 London 30
## 634 2020-12-03 London 27
## 635 2020-12-04 London 30
## 636 2020-12-05 London 26
## 637 2020-12-06 London 25
## 638 2020-12-07 London 29
## 639 2020-12-08 London 35
## 640 2020-12-09 London 28
## 641 2020-12-10 London 31
## 642 2020-12-11 London 27
## 643 2020-12-12 London 33
## 644 2020-12-13 London 33
## 645 2020-12-14 London 39
## 646 2020-12-15 London 49
## 647 2020-12-16 London 37
## 648 2020-12-17 London 57
## 649 2020-12-18 London 43
## 650 2020-12-19 London 41
## 651 2020-12-20 London 54
## 652 2020-12-21 London 60
## 653 2020-12-22 London 59
## 654 2020-12-23 London 57
## 655 2020-12-24 London 65
## 656 2020-12-25 London 82
## 657 2020-12-26 London 82
## 658 2020-12-27 London 92
## 659 2020-12-28 London 89
## 660 2020-12-29 London 110
## 661 2020-12-30 London 100
## 662 2020-12-31 London 110
## 663 2021-01-01 London 114
## 664 2021-01-02 London 126
## 665 2021-01-03 London 107
## 666 2021-01-04 London 148
## 667 2021-01-05 London 145
## 668 2021-01-06 London 146
## 669 2021-01-07 London 157
## 670 2021-01-08 London 138
## 671 2021-01-09 London 146
## 672 2021-01-10 London 160
## 673 2021-01-11 London 158
## 674 2021-01-12 London 170
## 675 2021-01-13 London 165
## 676 2021-01-14 London 154
## 677 2021-01-15 London 144
## 678 2021-01-16 London 158
## 679 2021-01-17 London 168
## 680 2021-01-18 London 182
## 681 2021-01-19 London 180
## 682 2021-01-20 London 155
## 683 2021-01-21 London 178
## 684 2021-01-22 London 139
## 685 2021-01-23 London 140
## 686 2021-01-24 London 128
## 687 2021-01-25 London 125
## 688 2021-01-26 London 118
## 689 2021-01-27 London 111
## 690 2021-01-28 London 108
## 691 2021-01-29 London 94
## 692 2021-01-30 London 88
## 693 2021-01-31 London 89
## 694 2021-02-01 London 77
## 695 2021-02-02 London 99
## 696 2021-02-03 London 106
## 697 2021-02-04 London 63
## 698 2021-02-05 London 85
## 699 2021-02-06 London 61
## 700 2021-02-07 London 67
## 701 2021-02-08 London 66
## 702 2021-02-09 London 56
## 703 2021-02-10 London 66
## 704 2021-02-11 London 46
## 705 2021-02-12 London 51
## 706 2021-02-13 London 42
## 707 2021-02-14 London 41
## 708 2021-02-15 London 34
## 709 2021-02-16 London 43
## 710 2021-02-17 London 35
## 711 2021-02-18 London 22
## 712 2021-02-19 London 7
## 713 2020-03-01 Midlands 0
## 714 2020-03-02 Midlands 0
## 715 2020-03-03 Midlands 1
## 716 2020-03-04 Midlands 0
## 717 2020-03-05 Midlands 0
## 718 2020-03-06 Midlands 0
## 719 2020-03-07 Midlands 0
## 720 2020-03-08 Midlands 2
## 721 2020-03-09 Midlands 1
## 722 2020-03-10 Midlands 0
## 723 2020-03-11 Midlands 2
## 724 2020-03-12 Midlands 6
## 725 2020-03-13 Midlands 5
## 726 2020-03-14 Midlands 4
## 727 2020-03-15 Midlands 5
## 728 2020-03-16 Midlands 11
## 729 2020-03-17 Midlands 8
## 730 2020-03-18 Midlands 13
## 731 2020-03-19 Midlands 8
## 732 2020-03-20 Midlands 28
## 733 2020-03-21 Midlands 13
## 734 2020-03-22 Midlands 31
## 735 2020-03-23 Midlands 33
## 736 2020-03-24 Midlands 41
## 737 2020-03-25 Midlands 48
## 738 2020-03-26 Midlands 64
## 739 2020-03-27 Midlands 72
## 740 2020-03-28 Midlands 89
## 741 2020-03-29 Midlands 92
## 742 2020-03-30 Midlands 90
## 743 2020-03-31 Midlands 123
## 744 2020-04-01 Midlands 140
## 745 2020-04-02 Midlands 142
## 746 2020-04-03 Midlands 124
## 747 2020-04-04 Midlands 151
## 748 2020-04-05 Midlands 164
## 749 2020-04-06 Midlands 140
## 750 2020-04-07 Midlands 123
## 751 2020-04-08 Midlands 186
## 752 2020-04-09 Midlands 140
## 753 2020-04-10 Midlands 127
## 754 2020-04-11 Midlands 142
## 755 2020-04-12 Midlands 139
## 756 2020-04-13 Midlands 120
## 757 2020-04-14 Midlands 116
## 758 2020-04-15 Midlands 147
## 759 2020-04-16 Midlands 102
## 760 2020-04-17 Midlands 118
## 761 2020-04-18 Midlands 115
## 762 2020-04-19 Midlands 93
## 763 2020-04-20 Midlands 107
## 764 2020-04-21 Midlands 86
## 765 2020-04-22 Midlands 78
## 766 2020-04-23 Midlands 103
## 767 2020-04-24 Midlands 79
## 768 2020-04-25 Midlands 72
## 769 2020-04-26 Midlands 81
## 770 2020-04-27 Midlands 74
## 771 2020-04-28 Midlands 68
## 772 2020-04-29 Midlands 53
## 773 2020-04-30 Midlands 56
## 774 2020-05-01 Midlands 64
## 775 2020-05-02 Midlands 51
## 776 2020-05-03 Midlands 52
## 777 2020-05-04 Midlands 61
## 778 2020-05-05 Midlands 59
## 779 2020-05-06 Midlands 59
## 780 2020-05-07 Midlands 48
## 781 2020-05-08 Midlands 34
## 782 2020-05-09 Midlands 37
## 783 2020-05-10 Midlands 42
## 784 2020-05-11 Midlands 33
## 785 2020-05-12 Midlands 45
## 786 2020-05-13 Midlands 40
## 787 2020-05-14 Midlands 39
## 788 2020-05-15 Midlands 40
## 789 2020-05-16 Midlands 34
## 790 2020-05-17 Midlands 31
## 791 2020-05-18 Midlands 36
## 792 2020-05-19 Midlands 35
## 793 2020-05-20 Midlands 36
## 794 2020-05-21 Midlands 32
## 795 2020-05-22 Midlands 27
## 796 2020-05-23 Midlands 34
## 797 2020-05-24 Midlands 20
## 798 2020-05-25 Midlands 26
## 799 2020-05-26 Midlands 33
## 800 2020-05-27 Midlands 29
## 801 2020-05-28 Midlands 28
## 802 2020-05-29 Midlands 20
## 803 2020-05-30 Midlands 21
## 804 2020-05-31 Midlands 22
## 805 2020-06-01 Midlands 20
## 806 2020-06-02 Midlands 22
## 807 2020-06-03 Midlands 24
## 808 2020-06-04 Midlands 16
## 809 2020-06-05 Midlands 21
## 810 2020-06-06 Midlands 20
## 811 2020-06-07 Midlands 17
## 812 2020-06-08 Midlands 16
## 813 2020-06-09 Midlands 18
## 814 2020-06-10 Midlands 15
## 815 2020-06-11 Midlands 13
## 816 2020-06-12 Midlands 12
## 817 2020-06-13 Midlands 6
## 818 2020-06-14 Midlands 18
## 819 2020-06-15 Midlands 12
## 820 2020-06-16 Midlands 15
## 821 2020-06-17 Midlands 11
## 822 2020-06-18 Midlands 15
## 823 2020-06-19 Midlands 10
## 824 2020-06-20 Midlands 15
## 825 2020-06-21 Midlands 14
## 826 2020-06-22 Midlands 14
## 827 2020-06-23 Midlands 16
## 828 2020-06-24 Midlands 15
## 829 2020-06-25 Midlands 18
## 830 2020-06-26 Midlands 5
## 831 2020-06-27 Midlands 5
## 832 2020-06-28 Midlands 7
## 833 2020-06-29 Midlands 6
## 834 2020-06-30 Midlands 6
## 835 2020-07-01 Midlands 7
## 836 2020-07-02 Midlands 10
## 837 2020-07-03 Midlands 3
## 838 2020-07-04 Midlands 4
## 839 2020-07-05 Midlands 6
## 840 2020-07-06 Midlands 5
## 841 2020-07-07 Midlands 3
## 842 2020-07-08 Midlands 5
## 843 2020-07-09 Midlands 9
## 844 2020-07-10 Midlands 3
## 845 2020-07-11 Midlands 0
## 846 2020-07-12 Midlands 5
## 847 2020-07-13 Midlands 1
## 848 2020-07-14 Midlands 1
## 849 2020-07-15 Midlands 6
## 850 2020-07-16 Midlands 2
## 851 2020-07-17 Midlands 3
## 852 2020-07-18 Midlands 3
## 853 2020-07-19 Midlands 3
## 854 2020-07-20 Midlands 3
## 855 2020-07-21 Midlands 1
## 856 2020-07-22 Midlands 2
## 857 2020-07-23 Midlands 6
## 858 2020-07-24 Midlands 1
## 859 2020-07-25 Midlands 4
## 860 2020-07-26 Midlands 4
## 861 2020-07-27 Midlands 5
## 862 2020-07-28 Midlands 1
## 863 2020-07-29 Midlands 1
## 864 2020-07-30 Midlands 1
## 865 2020-07-31 Midlands 2
## 866 2020-08-01 Midlands 0
## 867 2020-08-02 Midlands 1
## 868 2020-08-03 Midlands 2
## 869 2020-08-04 Midlands 1
## 870 2020-08-05 Midlands 1
## 871 2020-08-06 Midlands 0
## 872 2020-08-07 Midlands 3
## 873 2020-08-08 Midlands 2
## 874 2020-08-09 Midlands 0
## 875 2020-08-10 Midlands 0
## 876 2020-08-11 Midlands 2
## 877 2020-08-12 Midlands 0
## 878 2020-08-13 Midlands 0
## 879 2020-08-14 Midlands 0
## 880 2020-08-15 Midlands 1
## 881 2020-08-16 Midlands 0
## 882 2020-08-17 Midlands 0
## 883 2020-08-18 Midlands 0
## 884 2020-08-19 Midlands 0
## 885 2020-08-20 Midlands 0
## 886 2020-08-21 Midlands 1
## 887 2020-08-22 Midlands 0
## 888 2020-08-23 Midlands 0
## 889 2020-08-24 Midlands 0
## 890 2020-08-25 Midlands 2
## 891 2020-08-26 Midlands 3
## 892 2020-08-27 Midlands 2
## 893 2020-08-28 Midlands 1
## 894 2020-08-29 Midlands 0
## 895 2020-08-30 Midlands 2
## 896 2020-08-31 Midlands 1
## 897 2020-09-01 Midlands 0
## 898 2020-09-02 Midlands 2
## 899 2020-09-03 Midlands 0
## 900 2020-09-04 Midlands 0
## 901 2020-09-05 Midlands 0
## 902 2020-09-06 Midlands 1
## 903 2020-09-07 Midlands 1
## 904 2020-09-08 Midlands 3
## 905 2020-09-09 Midlands 0
## 906 2020-09-10 Midlands 1
## 907 2020-09-11 Midlands 1
## 908 2020-09-12 Midlands 2
## 909 2020-09-13 Midlands 4
## 910 2020-09-14 Midlands 1
## 911 2020-09-15 Midlands 2
## 912 2020-09-16 Midlands 3
## 913 2020-09-17 Midlands 2
## 914 2020-09-18 Midlands 5
## 915 2020-09-19 Midlands 2
## 916 2020-09-20 Midlands 7
## 917 2020-09-21 Midlands 3
## 918 2020-09-22 Midlands 4
## 919 2020-09-23 Midlands 10
## 920 2020-09-24 Midlands 7
## 921 2020-09-25 Midlands 4
## 922 2020-09-26 Midlands 5
## 923 2020-09-27 Midlands 9
## 924 2020-09-28 Midlands 6
## 925 2020-09-29 Midlands 4
## 926 2020-09-30 Midlands 5
## 927 2020-10-01 Midlands 8
## 928 2020-10-02 Midlands 7
## 929 2020-10-03 Midlands 6
## 930 2020-10-04 Midlands 7
## 931 2020-10-05 Midlands 6
## 932 2020-10-06 Midlands 5
## 933 2020-10-07 Midlands 9
## 934 2020-10-08 Midlands 8
## 935 2020-10-09 Midlands 7
## 936 2020-10-10 Midlands 2
## 937 2020-10-11 Midlands 15
## 938 2020-10-12 Midlands 7
## 939 2020-10-13 Midlands 16
## 940 2020-10-14 Midlands 12
## 941 2020-10-15 Midlands 11
## 942 2020-10-16 Midlands 18
## 943 2020-10-17 Midlands 25
## 944 2020-10-18 Midlands 11
## 945 2020-10-19 Midlands 14
## 946 2020-10-20 Midlands 19
## 947 2020-10-21 Midlands 15
## 948 2020-10-22 Midlands 34
## 949 2020-10-23 Midlands 32
## 950 2020-10-24 Midlands 24
## 951 2020-10-25 Midlands 30
## 952 2020-10-26 Midlands 33
## 953 2020-10-27 Midlands 38
## 954 2020-10-28 Midlands 30
## 955 2020-10-29 Midlands 42
## 956 2020-10-30 Midlands 42
## 957 2020-10-31 Midlands 50
## 958 2020-11-01 Midlands 44
## 959 2020-11-02 Midlands 58
## 960 2020-11-03 Midlands 37
## 961 2020-11-04 Midlands 67
## 962 2020-11-05 Midlands 50
## 963 2020-11-06 Midlands 43
## 964 2020-11-07 Midlands 60
## 965 2020-11-08 Midlands 55
## 966 2020-11-09 Midlands 67
## 967 2020-11-10 Midlands 68
## 968 2020-11-11 Midlands 58
## 969 2020-11-12 Midlands 64
## 970 2020-11-13 Midlands 47
## 971 2020-11-14 Midlands 66
## 972 2020-11-15 Midlands 72
## 973 2020-11-16 Midlands 66
## 974 2020-11-17 Midlands 66
## 975 2020-11-18 Midlands 83
## 976 2020-11-19 Midlands 72
## 977 2020-11-20 Midlands 87
## 978 2020-11-21 Midlands 59
## 979 2020-11-22 Midlands 84
## 980 2020-11-23 Midlands 80
## 981 2020-11-24 Midlands 73
## 982 2020-11-25 Midlands 74
## 983 2020-11-26 Midlands 77
## 984 2020-11-27 Midlands 78
## 985 2020-11-28 Midlands 80
## 986 2020-11-29 Midlands 86
## 987 2020-11-30 Midlands 79
## 988 2020-12-01 Midlands 74
## 989 2020-12-02 Midlands 64
## 990 2020-12-03 Midlands 82
## 991 2020-12-04 Midlands 67
## 992 2020-12-05 Midlands 71
## 993 2020-12-06 Midlands 75
## 994 2020-12-07 Midlands 68
## 995 2020-12-08 Midlands 66
## 996 2020-12-09 Midlands 63
## 997 2020-12-10 Midlands 75
## 998 2020-12-11 Midlands 65
## 999 2020-12-12 Midlands 81
## 1000 2020-12-13 Midlands 78
## 1001 2020-12-14 Midlands 77
## 1002 2020-12-15 Midlands 73
## 1003 2020-12-16 Midlands 73
## 1004 2020-12-17 Midlands 86
## 1005 2020-12-18 Midlands 80
## 1006 2020-12-19 Midlands 57
## 1007 2020-12-20 Midlands 66
## 1008 2020-12-21 Midlands 85
## 1009 2020-12-22 Midlands 74
## 1010 2020-12-23 Midlands 58
## 1011 2020-12-24 Midlands 68
## 1012 2020-12-25 Midlands 79
## 1013 2020-12-26 Midlands 74
## 1014 2020-12-27 Midlands 87
## 1015 2020-12-28 Midlands 64
## 1016 2020-12-29 Midlands 83
## 1017 2020-12-30 Midlands 100
## 1018 2020-12-31 Midlands 89
## 1019 2021-01-01 Midlands 77
## 1020 2021-01-02 Midlands 75
## 1021 2021-01-03 Midlands 71
## 1022 2021-01-04 Midlands 94
## 1023 2021-01-05 Midlands 105
## 1024 2021-01-06 Midlands 112
## 1025 2021-01-07 Midlands 103
## 1026 2021-01-08 Midlands 131
## 1027 2021-01-09 Midlands 137
## 1028 2021-01-10 Midlands 119
## 1029 2021-01-11 Midlands 142
## 1030 2021-01-12 Midlands 158
## 1031 2021-01-13 Midlands 140
## 1032 2021-01-14 Midlands 155
## 1033 2021-01-15 Midlands 130
## 1034 2021-01-16 Midlands 150
## 1035 2021-01-17 Midlands 156
## 1036 2021-01-18 Midlands 159
## 1037 2021-01-19 Midlands 157
## 1038 2021-01-20 Midlands 146
## 1039 2021-01-21 Midlands 156
## 1040 2021-01-22 Midlands 158
## 1041 2021-01-23 Midlands 141
## 1042 2021-01-24 Midlands 165
## 1043 2021-01-25 Midlands 154
## 1044 2021-01-26 Midlands 140
## 1045 2021-01-27 Midlands 136
## 1046 2021-01-28 Midlands 133
## 1047 2021-01-29 Midlands 147
## 1048 2021-01-30 Midlands 123
## 1049 2021-01-31 Midlands 109
## 1050 2021-02-01 Midlands 136
## 1051 2021-02-02 Midlands 131
## 1052 2021-02-03 Midlands 132
## 1053 2021-02-04 Midlands 109
## 1054 2021-02-05 Midlands 108
## 1055 2021-02-06 Midlands 91
## 1056 2021-02-07 Midlands 107
## 1057 2021-02-08 Midlands 99
## 1058 2021-02-09 Midlands 95
## 1059 2021-02-10 Midlands 92
## 1060 2021-02-11 Midlands 89
## 1061 2021-02-12 Midlands 86
## 1062 2021-02-13 Midlands 64
## 1063 2021-02-14 Midlands 78
## 1064 2021-02-15 Midlands 76
## 1065 2021-02-16 Midlands 67
## 1066 2021-02-17 Midlands 60
## 1067 2021-02-18 Midlands 50
## 1068 2021-02-19 Midlands 8
## 1069 2020-03-01 North East and Yorkshire 0
## 1070 2020-03-02 North East and Yorkshire 0
## 1071 2020-03-03 North East and Yorkshire 0
## 1072 2020-03-04 North East and Yorkshire 0
## 1073 2020-03-05 North East and Yorkshire 0
## 1074 2020-03-06 North East and Yorkshire 0
## 1075 2020-03-07 North East and Yorkshire 0
## 1076 2020-03-08 North East and Yorkshire 0
## 1077 2020-03-09 North East and Yorkshire 0
## 1078 2020-03-10 North East and Yorkshire 0
## 1079 2020-03-11 North East and Yorkshire 0
## 1080 2020-03-12 North East and Yorkshire 0
## 1081 2020-03-13 North East and Yorkshire 0
## 1082 2020-03-14 North East and Yorkshire 0
## 1083 2020-03-15 North East and Yorkshire 2
## 1084 2020-03-16 North East and Yorkshire 3
## 1085 2020-03-17 North East and Yorkshire 1
## 1086 2020-03-18 North East and Yorkshire 2
## 1087 2020-03-19 North East and Yorkshire 6
## 1088 2020-03-20 North East and Yorkshire 5
## 1089 2020-03-21 North East and Yorkshire 6
## 1090 2020-03-22 North East and Yorkshire 7
## 1091 2020-03-23 North East and Yorkshire 9
## 1092 2020-03-24 North East and Yorkshire 8
## 1093 2020-03-25 North East and Yorkshire 18
## 1094 2020-03-26 North East and Yorkshire 21
## 1095 2020-03-27 North East and Yorkshire 28
## 1096 2020-03-28 North East and Yorkshire 35
## 1097 2020-03-29 North East and Yorkshire 38
## 1098 2020-03-30 North East and Yorkshire 64
## 1099 2020-03-31 North East and Yorkshire 60
## 1100 2020-04-01 North East and Yorkshire 67
## 1101 2020-04-02 North East and Yorkshire 75
## 1102 2020-04-03 North East and Yorkshire 100
## 1103 2020-04-04 North East and Yorkshire 105
## 1104 2020-04-05 North East and Yorkshire 92
## 1105 2020-04-06 North East and Yorkshire 96
## 1106 2020-04-07 North East and Yorkshire 102
## 1107 2020-04-08 North East and Yorkshire 107
## 1108 2020-04-09 North East and Yorkshire 111
## 1109 2020-04-10 North East and Yorkshire 117
## 1110 2020-04-11 North East and Yorkshire 98
## 1111 2020-04-12 North East and Yorkshire 84
## 1112 2020-04-13 North East and Yorkshire 94
## 1113 2020-04-14 North East and Yorkshire 107
## 1114 2020-04-15 North East and Yorkshire 96
## 1115 2020-04-16 North East and Yorkshire 103
## 1116 2020-04-17 North East and Yorkshire 88
## 1117 2020-04-18 North East and Yorkshire 95
## 1118 2020-04-19 North East and Yorkshire 88
## 1119 2020-04-20 North East and Yorkshire 100
## 1120 2020-04-21 North East and Yorkshire 76
## 1121 2020-04-22 North East and Yorkshire 84
## 1122 2020-04-23 North East and Yorkshire 63
## 1123 2020-04-24 North East and Yorkshire 72
## 1124 2020-04-25 North East and Yorkshire 69
## 1125 2020-04-26 North East and Yorkshire 65
## 1126 2020-04-27 North East and Yorkshire 65
## 1127 2020-04-28 North East and Yorkshire 57
## 1128 2020-04-29 North East and Yorkshire 69
## 1129 2020-04-30 North East and Yorkshire 57
## 1130 2020-05-01 North East and Yorkshire 64
## 1131 2020-05-02 North East and Yorkshire 48
## 1132 2020-05-03 North East and Yorkshire 40
## 1133 2020-05-04 North East and Yorkshire 49
## 1134 2020-05-05 North East and Yorkshire 40
## 1135 2020-05-06 North East and Yorkshire 51
## 1136 2020-05-07 North East and Yorkshire 45
## 1137 2020-05-08 North East and Yorkshire 42
## 1138 2020-05-09 North East and Yorkshire 44
## 1139 2020-05-10 North East and Yorkshire 40
## 1140 2020-05-11 North East and Yorkshire 29
## 1141 2020-05-12 North East and Yorkshire 27
## 1142 2020-05-13 North East and Yorkshire 28
## 1143 2020-05-14 North East and Yorkshire 31
## 1144 2020-05-15 North East and Yorkshire 32
## 1145 2020-05-16 North East and Yorkshire 35
## 1146 2020-05-17 North East and Yorkshire 26
## 1147 2020-05-18 North East and Yorkshire 30
## 1148 2020-05-19 North East and Yorkshire 27
## 1149 2020-05-20 North East and Yorkshire 22
## 1150 2020-05-21 North East and Yorkshire 33
## 1151 2020-05-22 North East and Yorkshire 22
## 1152 2020-05-23 North East and Yorkshire 18
## 1153 2020-05-24 North East and Yorkshire 26
## 1154 2020-05-25 North East and Yorkshire 21
## 1155 2020-05-26 North East and Yorkshire 21
## 1156 2020-05-27 North East and Yorkshire 23
## 1157 2020-05-28 North East and Yorkshire 21
## 1158 2020-05-29 North East and Yorkshire 25
## 1159 2020-05-30 North East and Yorkshire 20
## 1160 2020-05-31 North East and Yorkshire 20
## 1161 2020-06-01 North East and Yorkshire 17
## 1162 2020-06-02 North East and Yorkshire 23
## 1163 2020-06-03 North East and Yorkshire 24
## 1164 2020-06-04 North East and Yorkshire 17
## 1165 2020-06-05 North East and Yorkshire 18
## 1166 2020-06-06 North East and Yorkshire 21
## 1167 2020-06-07 North East and Yorkshire 14
## 1168 2020-06-08 North East and Yorkshire 11
## 1169 2020-06-09 North East and Yorkshire 12
## 1170 2020-06-10 North East and Yorkshire 19
## 1171 2020-06-11 North East and Yorkshire 7
## 1172 2020-06-12 North East and Yorkshire 9
## 1173 2020-06-13 North East and Yorkshire 10
## 1174 2020-06-14 North East and Yorkshire 11
## 1175 2020-06-15 North East and Yorkshire 9
## 1176 2020-06-16 North East and Yorkshire 10
## 1177 2020-06-17 North East and Yorkshire 9
## 1178 2020-06-18 North East and Yorkshire 11
## 1179 2020-06-19 North East and Yorkshire 6
## 1180 2020-06-20 North East and Yorkshire 5
## 1181 2020-06-21 North East and Yorkshire 4
## 1182 2020-06-22 North East and Yorkshire 7
## 1183 2020-06-23 North East and Yorkshire 8
## 1184 2020-06-24 North East and Yorkshire 10
## 1185 2020-06-25 North East and Yorkshire 4
## 1186 2020-06-26 North East and Yorkshire 8
## 1187 2020-06-27 North East and Yorkshire 4
## 1188 2020-06-28 North East and Yorkshire 5
## 1189 2020-06-29 North East and Yorkshire 2
## 1190 2020-06-30 North East and Yorkshire 7
## 1191 2020-07-01 North East and Yorkshire 1
## 1192 2020-07-02 North East and Yorkshire 5
## 1193 2020-07-03 North East and Yorkshire 4
## 1194 2020-07-04 North East and Yorkshire 4
## 1195 2020-07-05 North East and Yorkshire 3
## 1196 2020-07-06 North East and Yorkshire 2
## 1197 2020-07-07 North East and Yorkshire 3
## 1198 2020-07-08 North East and Yorkshire 3
## 1199 2020-07-09 North East and Yorkshire 0
## 1200 2020-07-10 North East and Yorkshire 3
## 1201 2020-07-11 North East and Yorkshire 1
## 1202 2020-07-12 North East and Yorkshire 4
## 1203 2020-07-13 North East and Yorkshire 1
## 1204 2020-07-14 North East and Yorkshire 1
## 1205 2020-07-15 North East and Yorkshire 2
## 1206 2020-07-16 North East and Yorkshire 3
## 1207 2020-07-17 North East and Yorkshire 1
## 1208 2020-07-18 North East and Yorkshire 2
## 1209 2020-07-19 North East and Yorkshire 2
## 1210 2020-07-20 North East and Yorkshire 1
## 1211 2020-07-21 North East and Yorkshire 1
## 1212 2020-07-22 North East and Yorkshire 6
## 1213 2020-07-23 North East and Yorkshire 0
## 1214 2020-07-24 North East and Yorkshire 1
## 1215 2020-07-25 North East and Yorkshire 5
## 1216 2020-07-26 North East and Yorkshire 1
## 1217 2020-07-27 North East and Yorkshire 0
## 1218 2020-07-28 North East and Yorkshire 2
## 1219 2020-07-29 North East and Yorkshire 1
## 1220 2020-07-30 North East and Yorkshire 0
## 1221 2020-07-31 North East and Yorkshire 1
## 1222 2020-08-01 North East and Yorkshire 3
## 1223 2020-08-02 North East and Yorkshire 2
## 1224 2020-08-03 North East and Yorkshire 1
## 1225 2020-08-04 North East and Yorkshire 3
## 1226 2020-08-05 North East and Yorkshire 1
## 1227 2020-08-06 North East and Yorkshire 4
## 1228 2020-08-07 North East and Yorkshire 0
## 1229 2020-08-08 North East and Yorkshire 2
## 1230 2020-08-09 North East and Yorkshire 3
## 1231 2020-08-10 North East and Yorkshire 3
## 1232 2020-08-11 North East and Yorkshire 2
## 1233 2020-08-12 North East and Yorkshire 2
## 1234 2020-08-13 North East and Yorkshire 0
## 1235 2020-08-14 North East and Yorkshire 1
## 1236 2020-08-15 North East and Yorkshire 1
## 1237 2020-08-16 North East and Yorkshire 0
## 1238 2020-08-17 North East and Yorkshire 6
## 1239 2020-08-18 North East and Yorkshire 1
## 1240 2020-08-19 North East and Yorkshire 0
## 1241 2020-08-20 North East and Yorkshire 0
## 1242 2020-08-21 North East and Yorkshire 1
## 1243 2020-08-22 North East and Yorkshire 1
## 1244 2020-08-23 North East and Yorkshire 3
## 1245 2020-08-24 North East and Yorkshire 0
## 1246 2020-08-25 North East and Yorkshire 2
## 1247 2020-08-26 North East and Yorkshire 2
## 1248 2020-08-27 North East and Yorkshire 1
## 1249 2020-08-28 North East and Yorkshire 0
## 1250 2020-08-29 North East and Yorkshire 1
## 1251 2020-08-30 North East and Yorkshire 0
## 1252 2020-08-31 North East and Yorkshire 0
## 1253 2020-09-01 North East and Yorkshire 2
## 1254 2020-09-02 North East and Yorkshire 3
## 1255 2020-09-03 North East and Yorkshire 1
## 1256 2020-09-04 North East and Yorkshire 1
## 1257 2020-09-05 North East and Yorkshire 2
## 1258 2020-09-06 North East and Yorkshire 1
## 1259 2020-09-07 North East and Yorkshire 0
## 1260 2020-09-08 North East and Yorkshire 1
## 1261 2020-09-09 North East and Yorkshire 2
## 1262 2020-09-10 North East and Yorkshire 0
## 1263 2020-09-11 North East and Yorkshire 3
## 1264 2020-09-12 North East and Yorkshire 1
## 1265 2020-09-13 North East and Yorkshire 3
## 1266 2020-09-14 North East and Yorkshire 4
## 1267 2020-09-15 North East and Yorkshire 3
## 1268 2020-09-16 North East and Yorkshire 3
## 1269 2020-09-17 North East and Yorkshire 5
## 1270 2020-09-18 North East and Yorkshire 6
## 1271 2020-09-19 North East and Yorkshire 2
## 1272 2020-09-20 North East and Yorkshire 9
## 1273 2020-09-21 North East and Yorkshire 7
## 1274 2020-09-22 North East and Yorkshire 5
## 1275 2020-09-23 North East and Yorkshire 6
## 1276 2020-09-24 North East and Yorkshire 3
## 1277 2020-09-25 North East and Yorkshire 5
## 1278 2020-09-26 North East and Yorkshire 7
## 1279 2020-09-27 North East and Yorkshire 10
## 1280 2020-09-28 North East and Yorkshire 6
## 1281 2020-09-29 North East and Yorkshire 7
## 1282 2020-09-30 North East and Yorkshire 7
## 1283 2020-10-01 North East and Yorkshire 8
## 1284 2020-10-02 North East and Yorkshire 16
## 1285 2020-10-03 North East and Yorkshire 12
## 1286 2020-10-04 North East and Yorkshire 13
## 1287 2020-10-05 North East and Yorkshire 10
## 1288 2020-10-06 North East and Yorkshire 15
## 1289 2020-10-07 North East and Yorkshire 13
## 1290 2020-10-08 North East and Yorkshire 16
## 1291 2020-10-09 North East and Yorkshire 10
## 1292 2020-10-10 North East and Yorkshire 16
## 1293 2020-10-11 North East and Yorkshire 16
## 1294 2020-10-12 North East and Yorkshire 15
## 1295 2020-10-13 North East and Yorkshire 21
## 1296 2020-10-14 North East and Yorkshire 20
## 1297 2020-10-15 North East and Yorkshire 23
## 1298 2020-10-16 North East and Yorkshire 24
## 1299 2020-10-17 North East and Yorkshire 34
## 1300 2020-10-18 North East and Yorkshire 22
## 1301 2020-10-19 North East and Yorkshire 34
## 1302 2020-10-20 North East and Yorkshire 37
## 1303 2020-10-21 North East and Yorkshire 43
## 1304 2020-10-22 North East and Yorkshire 33
## 1305 2020-10-23 North East and Yorkshire 31
## 1306 2020-10-24 North East and Yorkshire 34
## 1307 2020-10-25 North East and Yorkshire 35
## 1308 2020-10-26 North East and Yorkshire 46
## 1309 2020-10-27 North East and Yorkshire 45
## 1310 2020-10-28 North East and Yorkshire 39
## 1311 2020-10-29 North East and Yorkshire 51
## 1312 2020-10-30 North East and Yorkshire 48
## 1313 2020-10-31 North East and Yorkshire 58
## 1314 2020-11-01 North East and Yorkshire 48
## 1315 2020-11-02 North East and Yorkshire 50
## 1316 2020-11-03 North East and Yorkshire 48
## 1317 2020-11-04 North East and Yorkshire 57
## 1318 2020-11-05 North East and Yorkshire 57
## 1319 2020-11-06 North East and Yorkshire 57
## 1320 2020-11-07 North East and Yorkshire 75
## 1321 2020-11-08 North East and Yorkshire 62
## 1322 2020-11-09 North East and Yorkshire 87
## 1323 2020-11-10 North East and Yorkshire 65
## 1324 2020-11-11 North East and Yorkshire 59
## 1325 2020-11-12 North East and Yorkshire 77
## 1326 2020-11-13 North East and Yorkshire 78
## 1327 2020-11-14 North East and Yorkshire 72
## 1328 2020-11-15 North East and Yorkshire 77
## 1329 2020-11-16 North East and Yorkshire 52
## 1330 2020-11-17 North East and Yorkshire 68
## 1331 2020-11-18 North East and Yorkshire 81
## 1332 2020-11-19 North East and Yorkshire 72
## 1333 2020-11-20 North East and Yorkshire 75
## 1334 2020-11-21 North East and Yorkshire 54
## 1335 2020-11-22 North East and Yorkshire 80
## 1336 2020-11-23 North East and Yorkshire 84
## 1337 2020-11-24 North East and Yorkshire 81
## 1338 2020-11-25 North East and Yorkshire 70
## 1339 2020-11-26 North East and Yorkshire 64
## 1340 2020-11-27 North East and Yorkshire 62
## 1341 2020-11-28 North East and Yorkshire 77
## 1342 2020-11-29 North East and Yorkshire 61
## 1343 2020-11-30 North East and Yorkshire 56
## 1344 2020-12-01 North East and Yorkshire 44
## 1345 2020-12-02 North East and Yorkshire 59
## 1346 2020-12-03 North East and Yorkshire 71
## 1347 2020-12-04 North East and Yorkshire 65
## 1348 2020-12-05 North East and Yorkshire 48
## 1349 2020-12-06 North East and Yorkshire 65
## 1350 2020-12-07 North East and Yorkshire 49
## 1351 2020-12-08 North East and Yorkshire 54
## 1352 2020-12-09 North East and Yorkshire 49
## 1353 2020-12-10 North East and Yorkshire 55
## 1354 2020-12-11 North East and Yorkshire 56
## 1355 2020-12-12 North East and Yorkshire 55
## 1356 2020-12-13 North East and Yorkshire 51
## 1357 2020-12-14 North East and Yorkshire 49
## 1358 2020-12-15 North East and Yorkshire 55
## 1359 2020-12-16 North East and Yorkshire 40
## 1360 2020-12-17 North East and Yorkshire 49
## 1361 2020-12-18 North East and Yorkshire 58
## 1362 2020-12-19 North East and Yorkshire 49
## 1363 2020-12-20 North East and Yorkshire 52
## 1364 2020-12-21 North East and Yorkshire 35
## 1365 2020-12-22 North East and Yorkshire 57
## 1366 2020-12-23 North East and Yorkshire 59
## 1367 2020-12-24 North East and Yorkshire 50
## 1368 2020-12-25 North East and Yorkshire 56
## 1369 2020-12-26 North East and Yorkshire 67
## 1370 2020-12-27 North East and Yorkshire 72
## 1371 2020-12-28 North East and Yorkshire 63
## 1372 2020-12-29 North East and Yorkshire 58
## 1373 2020-12-30 North East and Yorkshire 41
## 1374 2020-12-31 North East and Yorkshire 51
## 1375 2021-01-01 North East and Yorkshire 70
## 1376 2021-01-02 North East and Yorkshire 57
## 1377 2021-01-03 North East and Yorkshire 48
## 1378 2021-01-04 North East and Yorkshire 63
## 1379 2021-01-05 North East and Yorkshire 64
## 1380 2021-01-06 North East and Yorkshire 60
## 1381 2021-01-07 North East and Yorkshire 72
## 1382 2021-01-08 North East and Yorkshire 67
## 1383 2021-01-09 North East and Yorkshire 58
## 1384 2021-01-10 North East and Yorkshire 79
## 1385 2021-01-11 North East and Yorkshire 82
## 1386 2021-01-12 North East and Yorkshire 67
## 1387 2021-01-13 North East and Yorkshire 76
## 1388 2021-01-14 North East and Yorkshire 69
## 1389 2021-01-15 North East and Yorkshire 96
## 1390 2021-01-16 North East and Yorkshire 99
## 1391 2021-01-17 North East and Yorkshire 74
## 1392 2021-01-18 North East and Yorkshire 82
## 1393 2021-01-19 North East and Yorkshire 103
## 1394 2021-01-20 North East and Yorkshire 92
## 1395 2021-01-21 North East and Yorkshire 87
## 1396 2021-01-22 North East and Yorkshire 78
## 1397 2021-01-23 North East and Yorkshire 67
## 1398 2021-01-24 North East and Yorkshire 61
## 1399 2021-01-25 North East and Yorkshire 79
## 1400 2021-01-26 North East and Yorkshire 71
## 1401 2021-01-27 North East and Yorkshire 64
## 1402 2021-01-28 North East and Yorkshire 68
## 1403 2021-01-29 North East and Yorkshire 75
## 1404 2021-01-30 North East and Yorkshire 69
## 1405 2021-01-31 North East and Yorkshire 73
## 1406 2021-02-01 North East and Yorkshire 74
## 1407 2021-02-02 North East and Yorkshire 65
## 1408 2021-02-03 North East and Yorkshire 75
## 1409 2021-02-04 North East and Yorkshire 65
## 1410 2021-02-05 North East and Yorkshire 70
## 1411 2021-02-06 North East and Yorkshire 51
## 1412 2021-02-07 North East and Yorkshire 55
## 1413 2021-02-08 North East and Yorkshire 47
## 1414 2021-02-09 North East and Yorkshire 47
## 1415 2021-02-10 North East and Yorkshire 59
## 1416 2021-02-11 North East and Yorkshire 59
## 1417 2021-02-12 North East and Yorkshire 51
## 1418 2021-02-13 North East and Yorkshire 48
## 1419 2021-02-14 North East and Yorkshire 56
## 1420 2021-02-15 North East and Yorkshire 55
## 1421 2021-02-16 North East and Yorkshire 39
## 1422 2021-02-17 North East and Yorkshire 43
## 1423 2021-02-18 North East and Yorkshire 34
## 1424 2021-02-19 North East and Yorkshire 4
## 1425 2020-03-01 North West 0
## 1426 2020-03-02 North West 0
## 1427 2020-03-03 North West 0
## 1428 2020-03-04 North West 0
## 1429 2020-03-05 North West 1
## 1430 2020-03-06 North West 0
## 1431 2020-03-07 North West 0
## 1432 2020-03-08 North West 1
## 1433 2020-03-09 North West 0
## 1434 2020-03-10 North West 0
## 1435 2020-03-11 North West 0
## 1436 2020-03-12 North West 2
## 1437 2020-03-13 North West 3
## 1438 2020-03-14 North West 1
## 1439 2020-03-15 North West 4
## 1440 2020-03-16 North West 2
## 1441 2020-03-17 North West 4
## 1442 2020-03-18 North West 6
## 1443 2020-03-19 North West 7
## 1444 2020-03-20 North West 10
## 1445 2020-03-21 North West 11
## 1446 2020-03-22 North West 13
## 1447 2020-03-23 North West 15
## 1448 2020-03-24 North West 21
## 1449 2020-03-25 North West 21
## 1450 2020-03-26 North West 29
## 1451 2020-03-27 North West 36
## 1452 2020-03-28 North West 28
## 1453 2020-03-29 North West 46
## 1454 2020-03-30 North West 67
## 1455 2020-03-31 North West 52
## 1456 2020-04-01 North West 86
## 1457 2020-04-02 North West 96
## 1458 2020-04-03 North West 95
## 1459 2020-04-04 North West 98
## 1460 2020-04-05 North West 102
## 1461 2020-04-06 North West 100
## 1462 2020-04-07 North West 136
## 1463 2020-04-08 North West 127
## 1464 2020-04-09 North West 119
## 1465 2020-04-10 North West 117
## 1466 2020-04-11 North West 138
## 1467 2020-04-12 North West 125
## 1468 2020-04-13 North West 130
## 1469 2020-04-14 North West 130
## 1470 2020-04-15 North West 114
## 1471 2020-04-16 North West 135
## 1472 2020-04-17 North West 98
## 1473 2020-04-18 North West 114
## 1474 2020-04-19 North West 71
## 1475 2020-04-20 North West 83
## 1476 2020-04-21 North West 76
## 1477 2020-04-22 North West 87
## 1478 2020-04-23 North West 85
## 1479 2020-04-24 North West 67
## 1480 2020-04-25 North West 67
## 1481 2020-04-26 North West 55
## 1482 2020-04-27 North West 54
## 1483 2020-04-28 North West 57
## 1484 2020-04-29 North West 64
## 1485 2020-04-30 North West 60
## 1486 2020-05-01 North West 45
## 1487 2020-05-02 North West 56
## 1488 2020-05-03 North West 55
## 1489 2020-05-04 North West 48
## 1490 2020-05-05 North West 49
## 1491 2020-05-06 North West 44
## 1492 2020-05-07 North West 50
## 1493 2020-05-08 North West 43
## 1494 2020-05-09 North West 31
## 1495 2020-05-10 North West 42
## 1496 2020-05-11 North West 35
## 1497 2020-05-12 North West 38
## 1498 2020-05-13 North West 25
## 1499 2020-05-14 North West 26
## 1500 2020-05-15 North West 33
## 1501 2020-05-16 North West 32
## 1502 2020-05-17 North West 24
## 1503 2020-05-18 North West 31
## 1504 2020-05-19 North West 35
## 1505 2020-05-20 North West 27
## 1506 2020-05-21 North West 28
## 1507 2020-05-22 North West 26
## 1508 2020-05-23 North West 31
## 1509 2020-05-24 North West 26
## 1510 2020-05-25 North West 31
## 1511 2020-05-26 North West 27
## 1512 2020-05-27 North West 27
## 1513 2020-05-28 North West 28
## 1514 2020-05-29 North West 20
## 1515 2020-05-30 North West 19
## 1516 2020-05-31 North West 13
## 1517 2020-06-01 North West 12
## 1518 2020-06-02 North West 27
## 1519 2020-06-03 North West 22
## 1520 2020-06-04 North West 22
## 1521 2020-06-05 North West 16
## 1522 2020-06-06 North West 26
## 1523 2020-06-07 North West 20
## 1524 2020-06-08 North West 23
## 1525 2020-06-09 North West 17
## 1526 2020-06-10 North West 16
## 1527 2020-06-11 North West 16
## 1528 2020-06-12 North West 11
## 1529 2020-06-13 North West 10
## 1530 2020-06-14 North West 15
## 1531 2020-06-15 North West 16
## 1532 2020-06-16 North West 16
## 1533 2020-06-17 North West 13
## 1534 2020-06-18 North West 14
## 1535 2020-06-19 North West 7
## 1536 2020-06-20 North West 11
## 1537 2020-06-21 North West 8
## 1538 2020-06-22 North West 11
## 1539 2020-06-23 North West 13
## 1540 2020-06-24 North West 13
## 1541 2020-06-25 North West 15
## 1542 2020-06-26 North West 6
## 1543 2020-06-27 North West 7
## 1544 2020-06-28 North West 9
## 1545 2020-06-29 North West 9
## 1546 2020-06-30 North West 7
## 1547 2020-07-01 North West 3
## 1548 2020-07-02 North West 6
## 1549 2020-07-03 North West 7
## 1550 2020-07-04 North West 4
## 1551 2020-07-05 North West 6
## 1552 2020-07-06 North West 9
## 1553 2020-07-07 North West 8
## 1554 2020-07-08 North West 5
## 1555 2020-07-09 North West 10
## 1556 2020-07-10 North West 2
## 1557 2020-07-11 North West 5
## 1558 2020-07-12 North West 0
## 1559 2020-07-13 North West 6
## 1560 2020-07-14 North West 4
## 1561 2020-07-15 North West 5
## 1562 2020-07-16 North West 2
## 1563 2020-07-17 North West 4
## 1564 2020-07-18 North West 5
## 1565 2020-07-19 North West 3
## 1566 2020-07-20 North West 0
## 1567 2020-07-21 North West 2
## 1568 2020-07-22 North West 3
## 1569 2020-07-23 North West 3
## 1570 2020-07-24 North West 1
## 1571 2020-07-25 North West 1
## 1572 2020-07-26 North West 3
## 1573 2020-07-27 North West 1
## 1574 2020-07-28 North West 1
## 1575 2020-07-29 North West 2
## 1576 2020-07-30 North West 2
## 1577 2020-07-31 North West 0
## 1578 2020-08-01 North West 2
## 1579 2020-08-02 North West 1
## 1580 2020-08-03 North West 8
## 1581 2020-08-04 North West 3
## 1582 2020-08-05 North West 2
## 1583 2020-08-06 North West 2
## 1584 2020-08-07 North West 2
## 1585 2020-08-08 North West 2
## 1586 2020-08-09 North West 3
## 1587 2020-08-10 North West 2
## 1588 2020-08-11 North West 3
## 1589 2020-08-12 North West 0
## 1590 2020-08-13 North West 2
## 1591 2020-08-14 North West 2
## 1592 2020-08-15 North West 6
## 1593 2020-08-16 North West 2
## 1594 2020-08-17 North West 1
## 1595 2020-08-18 North West 2
## 1596 2020-08-19 North West 1
## 1597 2020-08-20 North West 1
## 1598 2020-08-21 North West 4
## 1599 2020-08-22 North West 3
## 1600 2020-08-23 North West 5
## 1601 2020-08-24 North West 4
## 1602 2020-08-25 North West 3
## 1603 2020-08-26 North West 4
## 1604 2020-08-27 North West 1
## 1605 2020-08-28 North West 2
## 1606 2020-08-29 North West 0
## 1607 2020-08-30 North West 2
## 1608 2020-08-31 North West 3
## 1609 2020-09-01 North West 0
## 1610 2020-09-02 North West 2
## 1611 2020-09-03 North West 1
## 1612 2020-09-04 North West 3
## 1613 2020-09-05 North West 6
## 1614 2020-09-06 North West 1
## 1615 2020-09-07 North West 8
## 1616 2020-09-08 North West 6
## 1617 2020-09-09 North West 5
## 1618 2020-09-10 North West 5
## 1619 2020-09-11 North West 1
## 1620 2020-09-12 North West 4
## 1621 2020-09-13 North West 2
## 1622 2020-09-14 North West 4
## 1623 2020-09-15 North West 4
## 1624 2020-09-16 North West 6
## 1625 2020-09-17 North West 7
## 1626 2020-09-18 North West 6
## 1627 2020-09-19 North West 3
## 1628 2020-09-20 North West 2
## 1629 2020-09-21 North West 2
## 1630 2020-09-22 North West 9
## 1631 2020-09-23 North West 14
## 1632 2020-09-24 North West 10
## 1633 2020-09-25 North West 8
## 1634 2020-09-26 North West 14
## 1635 2020-09-27 North West 11
## 1636 2020-09-28 North West 15
## 1637 2020-09-29 North West 12
## 1638 2020-09-30 North West 17
## 1639 2020-10-01 North West 17
## 1640 2020-10-02 North West 20
## 1641 2020-10-03 North West 15
## 1642 2020-10-04 North West 15
## 1643 2020-10-05 North West 15
## 1644 2020-10-06 North West 20
## 1645 2020-10-07 North West 20
## 1646 2020-10-08 North West 22
## 1647 2020-10-09 North West 24
## 1648 2020-10-10 North West 31
## 1649 2020-10-11 North West 31
## 1650 2020-10-12 North West 35
## 1651 2020-10-13 North West 26
## 1652 2020-10-14 North West 35
## 1653 2020-10-15 North West 36
## 1654 2020-10-16 North West 34
## 1655 2020-10-17 North West 52
## 1656 2020-10-18 North West 40
## 1657 2020-10-19 North West 43
## 1658 2020-10-20 North West 48
## 1659 2020-10-21 North West 51
## 1660 2020-10-22 North West 49
## 1661 2020-10-23 North West 50
## 1662 2020-10-24 North West 51
## 1663 2020-10-25 North West 63
## 1664 2020-10-26 North West 53
## 1665 2020-10-27 North West 49
## 1666 2020-10-28 North West 57
## 1667 2020-10-29 North West 74
## 1668 2020-10-30 North West 73
## 1669 2020-10-31 North West 63
## 1670 2020-11-01 North West 76
## 1671 2020-11-02 North West 65
## 1672 2020-11-03 North West 76
## 1673 2020-11-04 North West 64
## 1674 2020-11-05 North West 67
## 1675 2020-11-06 North West 76
## 1676 2020-11-07 North West 79
## 1677 2020-11-08 North West 83
## 1678 2020-11-09 North West 82
## 1679 2020-11-10 North West 68
## 1680 2020-11-11 North West 62
## 1681 2020-11-12 North West 64
## 1682 2020-11-13 North West 81
## 1683 2020-11-14 North West 61
## 1684 2020-11-15 North West 75
## 1685 2020-11-16 North West 74
## 1686 2020-11-17 North West 73
## 1687 2020-11-18 North West 71
## 1688 2020-11-19 North West 67
## 1689 2020-11-20 North West 52
## 1690 2020-11-21 North West 68
## 1691 2020-11-22 North West 52
## 1692 2020-11-23 North West 54
## 1693 2020-11-24 North West 64
## 1694 2020-11-25 North West 65
## 1695 2020-11-26 North West 53
## 1696 2020-11-27 North West 51
## 1697 2020-11-28 North West 46
## 1698 2020-11-29 North West 54
## 1699 2020-11-30 North West 48
## 1700 2020-12-01 North West 53
## 1701 2020-12-02 North West 48
## 1702 2020-12-03 North West 46
## 1703 2020-12-04 North West 48
## 1704 2020-12-05 North West 37
## 1705 2020-12-06 North West 43
## 1706 2020-12-07 North West 50
## 1707 2020-12-08 North West 49
## 1708 2020-12-09 North West 48
## 1709 2020-12-10 North West 49
## 1710 2020-12-11 North West 41
## 1711 2020-12-12 North West 48
## 1712 2020-12-13 North West 41
## 1713 2020-12-14 North West 51
## 1714 2020-12-15 North West 34
## 1715 2020-12-16 North West 41
## 1716 2020-12-17 North West 26
## 1717 2020-12-18 North West 47
## 1718 2020-12-19 North West 45
## 1719 2020-12-20 North West 37
## 1720 2020-12-21 North West 51
## 1721 2020-12-22 North West 52
## 1722 2020-12-23 North West 50
## 1723 2020-12-24 North West 58
## 1724 2020-12-25 North West 52
## 1725 2020-12-26 North West 56
## 1726 2020-12-27 North West 50
## 1727 2020-12-28 North West 48
## 1728 2020-12-29 North West 49
## 1729 2020-12-30 North West 49
## 1730 2020-12-31 North West 62
## 1731 2021-01-01 North West 54
## 1732 2021-01-02 North West 55
## 1733 2021-01-03 North West 57
## 1734 2021-01-04 North West 50
## 1735 2021-01-05 North West 55
## 1736 2021-01-06 North West 67
## 1737 2021-01-07 North West 61
## 1738 2021-01-08 North West 63
## 1739 2021-01-09 North West 64
## 1740 2021-01-10 North West 64
## 1741 2021-01-11 North West 77
## 1742 2021-01-12 North West 58
## 1743 2021-01-13 North West 84
## 1744 2021-01-14 North West 91
## 1745 2021-01-15 North West 82
## 1746 2021-01-16 North West 81
## 1747 2021-01-17 North West 79
## 1748 2021-01-18 North West 92
## 1749 2021-01-19 North West 88
## 1750 2021-01-20 North West 85
## 1751 2021-01-21 North West 84
## 1752 2021-01-22 North West 105
## 1753 2021-01-23 North West 99
## 1754 2021-01-24 North West 92
## 1755 2021-01-25 North West 82
## 1756 2021-01-26 North West 96
## 1757 2021-01-27 North West 103
## 1758 2021-01-28 North West 97
## 1759 2021-01-29 North West 91
## 1760 2021-01-30 North West 74
## 1761 2021-01-31 North West 82
## 1762 2021-02-01 North West 93
## 1763 2021-02-02 North West 80
## 1764 2021-02-03 North West 67
## 1765 2021-02-04 North West 75
## 1766 2021-02-05 North West 64
## 1767 2021-02-06 North West 56
## 1768 2021-02-07 North West 51
## 1769 2021-02-08 North West 73
## 1770 2021-02-09 North West 67
## 1771 2021-02-10 North West 70
## 1772 2021-02-11 North West 66
## 1773 2021-02-12 North West 66
## 1774 2021-02-13 North West 59
## 1775 2021-02-14 North West 50
## 1776 2021-02-15 North West 51
## 1777 2021-02-16 North West 45
## 1778 2021-02-17 North West 50
## 1779 2021-02-18 North West 39
## 1780 2021-02-19 North West 11
## 1781 2020-03-01 South East 0
## 1782 2020-03-02 South East 0
## 1783 2020-03-03 South East 1
## 1784 2020-03-04 South East 0
## 1785 2020-03-05 South East 1
## 1786 2020-03-06 South East 0
## 1787 2020-03-07 South East 0
## 1788 2020-03-08 South East 1
## 1789 2020-03-09 South East 1
## 1790 2020-03-10 South East 1
## 1791 2020-03-11 South East 1
## 1792 2020-03-12 South East 0
## 1793 2020-03-13 South East 1
## 1794 2020-03-14 South East 1
## 1795 2020-03-15 South East 5
## 1796 2020-03-16 South East 8
## 1797 2020-03-17 South East 7
## 1798 2020-03-18 South East 10
## 1799 2020-03-19 South East 9
## 1800 2020-03-20 South East 13
## 1801 2020-03-21 South East 7
## 1802 2020-03-22 South East 25
## 1803 2020-03-23 South East 20
## 1804 2020-03-24 South East 22
## 1805 2020-03-25 South East 29
## 1806 2020-03-26 South East 35
## 1807 2020-03-27 South East 36
## 1808 2020-03-28 South East 36
## 1809 2020-03-29 South East 55
## 1810 2020-03-30 South East 58
## 1811 2020-03-31 South East 65
## 1812 2020-04-01 South East 66
## 1813 2020-04-02 South East 55
## 1814 2020-04-03 South East 72
## 1815 2020-04-04 South East 80
## 1816 2020-04-05 South East 82
## 1817 2020-04-06 South East 88
## 1818 2020-04-07 South East 100
## 1819 2020-04-08 South East 83
## 1820 2020-04-09 South East 104
## 1821 2020-04-10 South East 88
## 1822 2020-04-11 South East 88
## 1823 2020-04-12 South East 88
## 1824 2020-04-13 South East 84
## 1825 2020-04-14 South East 65
## 1826 2020-04-15 South East 72
## 1827 2020-04-16 South East 56
## 1828 2020-04-17 South East 86
## 1829 2020-04-18 South East 57
## 1830 2020-04-19 South East 70
## 1831 2020-04-20 South East 87
## 1832 2020-04-21 South East 51
## 1833 2020-04-22 South East 54
## 1834 2020-04-23 South East 57
## 1835 2020-04-24 South East 64
## 1836 2020-04-25 South East 51
## 1837 2020-04-26 South East 51
## 1838 2020-04-27 South East 41
## 1839 2020-04-28 South East 40
## 1840 2020-04-29 South East 47
## 1841 2020-04-30 South East 29
## 1842 2020-05-01 South East 37
## 1843 2020-05-02 South East 36
## 1844 2020-05-03 South East 17
## 1845 2020-05-04 South East 35
## 1846 2020-05-05 South East 29
## 1847 2020-05-06 South East 25
## 1848 2020-05-07 South East 27
## 1849 2020-05-08 South East 26
## 1850 2020-05-09 South East 28
## 1851 2020-05-10 South East 19
## 1852 2020-05-11 South East 25
## 1853 2020-05-12 South East 27
## 1854 2020-05-13 South East 18
## 1855 2020-05-14 South East 32
## 1856 2020-05-15 South East 25
## 1857 2020-05-16 South East 22
## 1858 2020-05-17 South East 18
## 1859 2020-05-18 South East 23
## 1860 2020-05-19 South East 12
## 1861 2020-05-20 South East 22
## 1862 2020-05-21 South East 15
## 1863 2020-05-22 South East 17
## 1864 2020-05-23 South East 21
## 1865 2020-05-24 South East 17
## 1866 2020-05-25 South East 13
## 1867 2020-05-26 South East 19
## 1868 2020-05-27 South East 19
## 1869 2020-05-28 South East 12
## 1870 2020-05-29 South East 22
## 1871 2020-05-30 South East 8
## 1872 2020-05-31 South East 12
## 1873 2020-06-01 South East 11
## 1874 2020-06-02 South East 13
## 1875 2020-06-03 South East 18
## 1876 2020-06-04 South East 11
## 1877 2020-06-05 South East 11
## 1878 2020-06-06 South East 10
## 1879 2020-06-07 South East 12
## 1880 2020-06-08 South East 8
## 1881 2020-06-09 South East 11
## 1882 2020-06-10 South East 11
## 1883 2020-06-11 South East 5
## 1884 2020-06-12 South East 6
## 1885 2020-06-13 South East 7
## 1886 2020-06-14 South East 7
## 1887 2020-06-15 South East 8
## 1888 2020-06-16 South East 14
## 1889 2020-06-17 South East 10
## 1890 2020-06-18 South East 4
## 1891 2020-06-19 South East 7
## 1892 2020-06-20 South East 5
## 1893 2020-06-21 South East 3
## 1894 2020-06-22 South East 2
## 1895 2020-06-23 South East 9
## 1896 2020-06-24 South East 7
## 1897 2020-06-25 South East 5
## 1898 2020-06-26 South East 8
## 1899 2020-06-27 South East 9
## 1900 2020-06-28 South East 6
## 1901 2020-06-29 South East 5
## 1902 2020-06-30 South East 5
## 1903 2020-07-01 South East 2
## 1904 2020-07-02 South East 8
## 1905 2020-07-03 South East 3
## 1906 2020-07-04 South East 6
## 1907 2020-07-05 South East 5
## 1908 2020-07-06 South East 4
## 1909 2020-07-07 South East 6
## 1910 2020-07-08 South East 3
## 1911 2020-07-09 South East 7
## 1912 2020-07-10 South East 3
## 1913 2020-07-11 South East 4
## 1914 2020-07-12 South East 5
## 1915 2020-07-13 South East 5
## 1916 2020-07-14 South East 5
## 1917 2020-07-15 South East 6
## 1918 2020-07-16 South East 3
## 1919 2020-07-17 South East 1
## 1920 2020-07-18 South East 5
## 1921 2020-07-19 South East 2
## 1922 2020-07-20 South East 6
## 1923 2020-07-21 South East 4
## 1924 2020-07-22 South East 2
## 1925 2020-07-23 South East 3
## 1926 2020-07-24 South East 1
## 1927 2020-07-25 South East 1
## 1928 2020-07-26 South East 3
## 1929 2020-07-27 South East 1
## 1930 2020-07-28 South East 3
## 1931 2020-07-29 South East 2
## 1932 2020-07-30 South East 3
## 1933 2020-07-31 South East 1
## 1934 2020-08-01 South East 2
## 1935 2020-08-02 South East 4
## 1936 2020-08-03 South East 0
## 1937 2020-08-04 South East 0
## 1938 2020-08-05 South East 0
## 1939 2020-08-06 South East 2
## 1940 2020-08-07 South East 0
## 1941 2020-08-08 South East 2
## 1942 2020-08-09 South East 0
## 1943 2020-08-10 South East 2
## 1944 2020-08-11 South East 1
## 1945 2020-08-12 South East 1
## 1946 2020-08-13 South East 0
## 1947 2020-08-14 South East 0
## 1948 2020-08-15 South East 2
## 1949 2020-08-16 South East 1
## 1950 2020-08-17 South East 0
## 1951 2020-08-18 South East 2
## 1952 2020-08-19 South East 1
## 1953 2020-08-20 South East 0
## 1954 2020-08-21 South East 0
## 1955 2020-08-22 South East 0
## 1956 2020-08-23 South East 1
## 1957 2020-08-24 South East 0
## 1958 2020-08-25 South East 1
## 1959 2020-08-26 South East 0
## 1960 2020-08-27 South East 1
## 1961 2020-08-28 South East 2
## 1962 2020-08-29 South East 1
## 1963 2020-08-30 South East 0
## 1964 2020-08-31 South East 2
## 1965 2020-09-01 South East 1
## 1966 2020-09-02 South East 1
## 1967 2020-09-03 South East 0
## 1968 2020-09-04 South East 1
## 1969 2020-09-05 South East 0
## 1970 2020-09-06 South East 1
## 1971 2020-09-07 South East 0
## 1972 2020-09-08 South East 0
## 1973 2020-09-09 South East 0
## 1974 2020-09-10 South East 1
## 1975 2020-09-11 South East 1
## 1976 2020-09-12 South East 0
## 1977 2020-09-13 South East 3
## 1978 2020-09-14 South East 1
## 1979 2020-09-15 South East 2
## 1980 2020-09-16 South East 2
## 1981 2020-09-17 South East 3
## 1982 2020-09-18 South East 1
## 1983 2020-09-19 South East 1
## 1984 2020-09-20 South East 0
## 1985 2020-09-21 South East 3
## 1986 2020-09-22 South East 0
## 1987 2020-09-23 South East 2
## 1988 2020-09-24 South East 1
## 1989 2020-09-25 South East 3
## 1990 2020-09-26 South East 2
## 1991 2020-09-27 South East 2
## 1992 2020-09-28 South East 6
## 1993 2020-09-29 South East 3
## 1994 2020-09-30 South East 4
## 1995 2020-10-01 South East 4
## 1996 2020-10-02 South East 2
## 1997 2020-10-03 South East 1
## 1998 2020-10-04 South East 1
## 1999 2020-10-05 South East 2
## 2000 2020-10-06 South East 1
## 2001 2020-10-07 South East 4
## 2002 2020-10-08 South East 1
## 2003 2020-10-09 South East 1
## 2004 2020-10-10 South East 3
## 2005 2020-10-11 South East 3
## 2006 2020-10-12 South East 4
## 2007 2020-10-13 South East 2
## 2008 2020-10-14 South East 2
## 2009 2020-10-15 South East 3
## 2010 2020-10-16 South East 2
## 2011 2020-10-17 South East 3
## 2012 2020-10-18 South East 4
## 2013 2020-10-19 South East 7
## 2014 2020-10-20 South East 8
## 2015 2020-10-21 South East 9
## 2016 2020-10-22 South East 5
## 2017 2020-10-23 South East 7
## 2018 2020-10-24 South East 5
## 2019 2020-10-25 South East 9
## 2020 2020-10-26 South East 13
## 2021 2020-10-27 South East 10
## 2022 2020-10-28 South East 10
## 2023 2020-10-29 South East 7
## 2024 2020-10-30 South East 6
## 2025 2020-10-31 South East 15
## 2026 2020-11-01 South East 18
## 2027 2020-11-02 South East 13
## 2028 2020-11-03 South East 16
## 2029 2020-11-04 South East 10
## 2030 2020-11-05 South East 10
## 2031 2020-11-06 South East 16
## 2032 2020-11-07 South East 17
## 2033 2020-11-08 South East 18
## 2034 2020-11-09 South East 19
## 2035 2020-11-10 South East 20
## 2036 2020-11-11 South East 20
## 2037 2020-11-12 South East 20
## 2038 2020-11-13 South East 12
## 2039 2020-11-14 South East 24
## 2040 2020-11-15 South East 25
## 2041 2020-11-16 South East 22
## 2042 2020-11-17 South East 23
## 2043 2020-11-18 South East 26
## 2044 2020-11-19 South East 21
## 2045 2020-11-20 South East 18
## 2046 2020-11-21 South East 23
## 2047 2020-11-22 South East 30
## 2048 2020-11-23 South East 29
## 2049 2020-11-24 South East 26
## 2050 2020-11-25 South East 42
## 2051 2020-11-26 South East 30
## 2052 2020-11-27 South East 31
## 2053 2020-11-28 South East 24
## 2054 2020-11-29 South East 37
## 2055 2020-11-30 South East 23
## 2056 2020-12-01 South East 29
## 2057 2020-12-02 South East 33
## 2058 2020-12-03 South East 36
## 2059 2020-12-04 South East 41
## 2060 2020-12-05 South East 36
## 2061 2020-12-06 South East 32
## 2062 2020-12-07 South East 25
## 2063 2020-12-08 South East 43
## 2064 2020-12-09 South East 44
## 2065 2020-12-10 South East 38
## 2066 2020-12-11 South East 48
## 2067 2020-12-12 South East 40
## 2068 2020-12-13 South East 41
## 2069 2020-12-14 South East 38
## 2070 2020-12-15 South East 51
## 2071 2020-12-16 South East 45
## 2072 2020-12-17 South East 54
## 2073 2020-12-18 South East 48
## 2074 2020-12-19 South East 43
## 2075 2020-12-20 South East 57
## 2076 2020-12-21 South East 66
## 2077 2020-12-22 South East 62
## 2078 2020-12-23 South East 70
## 2079 2020-12-24 South East 56
## 2080 2020-12-25 South East 71
## 2081 2020-12-26 South East 75
## 2082 2020-12-27 South East 76
## 2083 2020-12-28 South East 81
## 2084 2020-12-29 South East 78
## 2085 2020-12-30 South East 92
## 2086 2020-12-31 South East 92
## 2087 2021-01-01 South East 60
## 2088 2021-01-02 South East 94
## 2089 2021-01-03 South East 79
## 2090 2021-01-04 South East 106
## 2091 2021-01-05 South East 107
## 2092 2021-01-06 South East 121
## 2093 2021-01-07 South East 116
## 2094 2021-01-08 South East 125
## 2095 2021-01-09 South East 115
## 2096 2021-01-10 South East 125
## 2097 2021-01-11 South East 128
## 2098 2021-01-12 South East 169
## 2099 2021-01-13 South East 133
## 2100 2021-01-14 South East 138
## 2101 2021-01-15 South East 125
## 2102 2021-01-16 South East 153
## 2103 2021-01-17 South East 165
## 2104 2021-01-18 South East 151
## 2105 2021-01-19 South East 154
## 2106 2021-01-20 South East 134
## 2107 2021-01-21 South East 132
## 2108 2021-01-22 South East 129
## 2109 2021-01-23 South East 122
## 2110 2021-01-24 South East 115
## 2111 2021-01-25 South East 112
## 2112 2021-01-26 South East 130
## 2113 2021-01-27 South East 111
## 2114 2021-01-28 South East 127
## 2115 2021-01-29 South East 107
## 2116 2021-01-30 South East 92
## 2117 2021-01-31 South East 93
## 2118 2021-02-01 South East 94
## 2119 2021-02-02 South East 82
## 2120 2021-02-03 South East 95
## 2121 2021-02-04 South East 58
## 2122 2021-02-05 South East 68
## 2123 2021-02-06 South East 73
## 2124 2021-02-07 South East 63
## 2125 2021-02-08 South East 67
## 2126 2021-02-09 South East 37
## 2127 2021-02-10 South East 46
## 2128 2021-02-11 South East 62
## 2129 2021-02-12 South East 43
## 2130 2021-02-13 South East 33
## 2131 2021-02-14 South East 41
## 2132 2021-02-15 South East 44
## 2133 2021-02-16 South East 35
## 2134 2021-02-17 South East 27
## 2135 2021-02-18 South East 19
## 2136 2021-02-19 South East 1
## 2137 2020-03-01 South West 0
## 2138 2020-03-02 South West 0
## 2139 2020-03-03 South West 0
## 2140 2020-03-04 South West 0
## 2141 2020-03-05 South West 0
## 2142 2020-03-06 South West 0
## 2143 2020-03-07 South West 0
## 2144 2020-03-08 South West 0
## 2145 2020-03-09 South West 0
## 2146 2020-03-10 South West 0
## 2147 2020-03-11 South West 1
## 2148 2020-03-12 South West 0
## 2149 2020-03-13 South West 0
## 2150 2020-03-14 South West 1
## 2151 2020-03-15 South West 0
## 2152 2020-03-16 South West 0
## 2153 2020-03-17 South West 2
## 2154 2020-03-18 South West 2
## 2155 2020-03-19 South West 4
## 2156 2020-03-20 South West 3
## 2157 2020-03-21 South West 6
## 2158 2020-03-22 South West 7
## 2159 2020-03-23 South West 8
## 2160 2020-03-24 South West 7
## 2161 2020-03-25 South West 9
## 2162 2020-03-26 South West 11
## 2163 2020-03-27 South West 13
## 2164 2020-03-28 South West 21
## 2165 2020-03-29 South West 18
## 2166 2020-03-30 South West 23
## 2167 2020-03-31 South West 23
## 2168 2020-04-01 South West 21
## 2169 2020-04-02 South West 23
## 2170 2020-04-03 South West 30
## 2171 2020-04-04 South West 42
## 2172 2020-04-05 South West 32
## 2173 2020-04-06 South West 34
## 2174 2020-04-07 South West 39
## 2175 2020-04-08 South West 47
## 2176 2020-04-09 South West 24
## 2177 2020-04-10 South West 46
## 2178 2020-04-11 South West 43
## 2179 2020-04-12 South West 23
## 2180 2020-04-13 South West 27
## 2181 2020-04-14 South West 24
## 2182 2020-04-15 South West 32
## 2183 2020-04-16 South West 29
## 2184 2020-04-17 South West 33
## 2185 2020-04-18 South West 25
## 2186 2020-04-19 South West 31
## 2187 2020-04-20 South West 26
## 2188 2020-04-21 South West 26
## 2189 2020-04-22 South West 23
## 2190 2020-04-23 South West 17
## 2191 2020-04-24 South West 19
## 2192 2020-04-25 South West 15
## 2193 2020-04-26 South West 27
## 2194 2020-04-27 South West 13
## 2195 2020-04-28 South West 17
## 2196 2020-04-29 South West 15
## 2197 2020-04-30 South West 26
## 2198 2020-05-01 South West 6
## 2199 2020-05-02 South West 7
## 2200 2020-05-03 South West 10
## 2201 2020-05-04 South West 17
## 2202 2020-05-05 South West 14
## 2203 2020-05-06 South West 19
## 2204 2020-05-07 South West 16
## 2205 2020-05-08 South West 6
## 2206 2020-05-09 South West 11
## 2207 2020-05-10 South West 5
## 2208 2020-05-11 South West 8
## 2209 2020-05-12 South West 7
## 2210 2020-05-13 South West 7
## 2211 2020-05-14 South West 6
## 2212 2020-05-15 South West 4
## 2213 2020-05-16 South West 4
## 2214 2020-05-17 South West 6
## 2215 2020-05-18 South West 4
## 2216 2020-05-19 South West 6
## 2217 2020-05-20 South West 1
## 2218 2020-05-21 South West 9
## 2219 2020-05-22 South West 7
## 2220 2020-05-23 South West 6
## 2221 2020-05-24 South West 3
## 2222 2020-05-25 South West 8
## 2223 2020-05-26 South West 11
## 2224 2020-05-27 South West 5
## 2225 2020-05-28 South West 10
## 2226 2020-05-29 South West 7
## 2227 2020-05-30 South West 3
## 2228 2020-05-31 South West 2
## 2229 2020-06-01 South West 7
## 2230 2020-06-02 South West 2
## 2231 2020-06-03 South West 7
## 2232 2020-06-04 South West 2
## 2233 2020-06-05 South West 2
## 2234 2020-06-06 South West 1
## 2235 2020-06-07 South West 3
## 2236 2020-06-08 South West 3
## 2237 2020-06-09 South West 0
## 2238 2020-06-10 South West 1
## 2239 2020-06-11 South West 2
## 2240 2020-06-12 South West 2
## 2241 2020-06-13 South West 2
## 2242 2020-06-14 South West 0
## 2243 2020-06-15 South West 2
## 2244 2020-06-16 South West 2
## 2245 2020-06-17 South West 0
## 2246 2020-06-18 South West 0
## 2247 2020-06-19 South West 0
## 2248 2020-06-20 South West 2
## 2249 2020-06-21 South West 0
## 2250 2020-06-22 South West 1
## 2251 2020-06-23 South West 1
## 2252 2020-06-24 South West 1
## 2253 2020-06-25 South West 0
## 2254 2020-06-26 South West 3
## 2255 2020-06-27 South West 0
## 2256 2020-06-28 South West 0
## 2257 2020-06-29 South West 1
## 2258 2020-06-30 South West 0
## 2259 2020-07-01 South West 0
## 2260 2020-07-02 South West 0
## 2261 2020-07-03 South West 0
## 2262 2020-07-04 South West 0
## 2263 2020-07-05 South West 1
## 2264 2020-07-06 South West 0
## 2265 2020-07-07 South West 0
## 2266 2020-07-08 South West 2
## 2267 2020-07-09 South West 0
## 2268 2020-07-10 South West 1
## 2269 2020-07-11 South West 0
## 2270 2020-07-12 South West 0
## 2271 2020-07-13 South West 1
## 2272 2020-07-14 South West 0
## 2273 2020-07-15 South West 0
## 2274 2020-07-16 South West 0
## 2275 2020-07-17 South West 1
## 2276 2020-07-18 South West 0
## 2277 2020-07-19 South West 0
## 2278 2020-07-20 South West 0
## 2279 2020-07-21 South West 0
## 2280 2020-07-22 South West 0
## 2281 2020-07-23 South West 0
## 2282 2020-07-24 South West 0
## 2283 2020-07-25 South West 0
## 2284 2020-07-26 South West 0
## 2285 2020-07-27 South West 0
## 2286 2020-07-28 South West 0
## 2287 2020-07-29 South West 0
## 2288 2020-07-30 South West 1
## 2289 2020-07-31 South West 0
## 2290 2020-08-01 South West 0
## 2291 2020-08-02 South West 0
## 2292 2020-08-03 South West 0
## 2293 2020-08-04 South West 0
## 2294 2020-08-05 South West 0
## 2295 2020-08-06 South West 0
## 2296 2020-08-07 South West 0
## 2297 2020-08-08 South West 0
## 2298 2020-08-09 South West 0
## 2299 2020-08-10 South West 0
## 2300 2020-08-11 South West 0
## 2301 2020-08-12 South West 0
## 2302 2020-08-13 South West 0
## 2303 2020-08-14 South West 1
## 2304 2020-08-15 South West 0
## 2305 2020-08-16 South West 0
## 2306 2020-08-17 South West 2
## 2307 2020-08-18 South West 0
## 2308 2020-08-19 South West 0
## 2309 2020-08-20 South West 0
## 2310 2020-08-21 South West 0
## 2311 2020-08-22 South West 0
## 2312 2020-08-23 South West 0
## 2313 2020-08-24 South West 0
## 2314 2020-08-25 South West 1
## 2315 2020-08-26 South West 0
## 2316 2020-08-27 South West 1
## 2317 2020-08-28 South West 0
## 2318 2020-08-29 South West 0
## 2319 2020-08-30 South West 0
## 2320 2020-08-31 South West 0
## 2321 2020-09-01 South West 0
## 2322 2020-09-02 South West 0
## 2323 2020-09-03 South West 0
## 2324 2020-09-04 South West 0
## 2325 2020-09-05 South West 0
## 2326 2020-09-06 South West 0
## 2327 2020-09-07 South West 0
## 2328 2020-09-08 South West 1
## 2329 2020-09-09 South West 0
## 2330 2020-09-10 South West 0
## 2331 2020-09-11 South West 0
## 2332 2020-09-12 South West 0
## 2333 2020-09-13 South West 1
## 2334 2020-09-14 South West 0
## 2335 2020-09-15 South West 0
## 2336 2020-09-16 South West 0
## 2337 2020-09-17 South West 1
## 2338 2020-09-18 South West 0
## 2339 2020-09-19 South West 0
## 2340 2020-09-20 South West 1
## 2341 2020-09-21 South West 0
## 2342 2020-09-22 South West 0
## 2343 2020-09-23 South West 0
## 2344 2020-09-24 South West 1
## 2345 2020-09-25 South West 0
## 2346 2020-09-26 South West 0
## 2347 2020-09-27 South West 0
## 2348 2020-09-28 South West 0
## 2349 2020-09-29 South West 0
## 2350 2020-09-30 South West 0
## 2351 2020-10-01 South West 0
## 2352 2020-10-02 South West 1
## 2353 2020-10-03 South West 0
## 2354 2020-10-04 South West 0
## 2355 2020-10-05 South West 0
## 2356 2020-10-06 South West 1
## 2357 2020-10-07 South West 0
## 2358 2020-10-08 South West 1
## 2359 2020-10-09 South West 1
## 2360 2020-10-10 South West 0
## 2361 2020-10-11 South West 4
## 2362 2020-10-12 South West 2
## 2363 2020-10-13 South West 0
## 2364 2020-10-14 South West 3
## 2365 2020-10-15 South West 1
## 2366 2020-10-16 South West 2
## 2367 2020-10-17 South West 8
## 2368 2020-10-18 South West 2
## 2369 2020-10-19 South West 2
## 2370 2020-10-20 South West 3
## 2371 2020-10-21 South West 6
## 2372 2020-10-22 South West 6
## 2373 2020-10-23 South West 5
## 2374 2020-10-24 South West 5
## 2375 2020-10-25 South West 5
## 2376 2020-10-26 South West 7
## 2377 2020-10-27 South West 6
## 2378 2020-10-28 South West 8
## 2379 2020-10-29 South West 11
## 2380 2020-10-30 South West 8
## 2381 2020-10-31 South West 4
## 2382 2020-11-01 South West 5
## 2383 2020-11-02 South West 11
## 2384 2020-11-03 South West 7
## 2385 2020-11-04 South West 8
## 2386 2020-11-05 South West 5
## 2387 2020-11-06 South West 11
## 2388 2020-11-07 South West 10
## 2389 2020-11-08 South West 10
## 2390 2020-11-09 South West 12
## 2391 2020-11-10 South West 6
## 2392 2020-11-11 South West 13
## 2393 2020-11-12 South West 17
## 2394 2020-11-13 South West 9
## 2395 2020-11-14 South West 8
## 2396 2020-11-15 South West 16
## 2397 2020-11-16 South West 18
## 2398 2020-11-17 South West 17
## 2399 2020-11-18 South West 26
## 2400 2020-11-19 South West 15
## 2401 2020-11-20 South West 25
## 2402 2020-11-21 South West 25
## 2403 2020-11-22 South West 24
## 2404 2020-11-23 South West 14
## 2405 2020-11-24 South West 20
## 2406 2020-11-25 South West 25
## 2407 2020-11-26 South West 16
## 2408 2020-11-27 South West 21
## 2409 2020-11-28 South West 35
## 2410 2020-11-29 South West 15
## 2411 2020-11-30 South West 22
## 2412 2020-12-01 South West 19
## 2413 2020-12-02 South West 15
## 2414 2020-12-03 South West 14
## 2415 2020-12-04 South West 20
## 2416 2020-12-05 South West 17
## 2417 2020-12-06 South West 13
## 2418 2020-12-07 South West 16
## 2419 2020-12-08 South West 19
## 2420 2020-12-09 South West 21
## 2421 2020-12-10 South West 20
## 2422 2020-12-11 South West 20
## 2423 2020-12-12 South West 15
## 2424 2020-12-13 South West 19
## 2425 2020-12-14 South West 20
## 2426 2020-12-15 South West 20
## 2427 2020-12-16 South West 9
## 2428 2020-12-17 South West 26
## 2429 2020-12-18 South West 11
## 2430 2020-12-19 South West 22
## 2431 2020-12-20 South West 19
## 2432 2020-12-21 South West 22
## 2433 2020-12-22 South West 10
## 2434 2020-12-23 South West 16
## 2435 2020-12-24 South West 18
## 2436 2020-12-25 South West 19
## 2437 2020-12-26 South West 24
## 2438 2020-12-27 South West 24
## 2439 2020-12-28 South West 21
## 2440 2020-12-29 South West 20
## 2441 2020-12-30 South West 17
## 2442 2020-12-31 South West 27
## 2443 2021-01-01 South West 29
## 2444 2021-01-02 South West 24
## 2445 2021-01-03 South West 28
## 2446 2021-01-04 South West 30
## 2447 2021-01-05 South West 31
## 2448 2021-01-06 South West 24
## 2449 2021-01-07 South West 29
## 2450 2021-01-08 South West 33
## 2451 2021-01-09 South West 26
## 2452 2021-01-10 South West 31
## 2453 2021-01-11 South West 36
## 2454 2021-01-12 South West 48
## 2455 2021-01-13 South West 40
## 2456 2021-01-14 South West 32
## 2457 2021-01-15 South West 44
## 2458 2021-01-16 South West 54
## 2459 2021-01-17 South West 32
## 2460 2021-01-18 South West 42
## 2461 2021-01-19 South West 43
## 2462 2021-01-20 South West 62
## 2463 2021-01-21 South West 54
## 2464 2021-01-22 South West 58
## 2465 2021-01-23 South West 53
## 2466 2021-01-24 South West 59
## 2467 2021-01-25 South West 55
## 2468 2021-01-26 South West 42
## 2469 2021-01-27 South West 40
## 2470 2021-01-28 South West 49
## 2471 2021-01-29 South West 41
## 2472 2021-01-30 South West 36
## 2473 2021-01-31 South West 35
## 2474 2021-02-01 South West 28
## 2475 2021-02-02 South West 35
## 2476 2021-02-03 South West 31
## 2477 2021-02-04 South West 31
## 2478 2021-02-05 South West 24
## 2479 2021-02-06 South West 38
## 2480 2021-02-07 South West 33
## 2481 2021-02-08 South West 30
## 2482 2021-02-09 South West 29
## 2483 2021-02-10 South West 17
## 2484 2021-02-11 South West 18
## 2485 2021-02-12 South West 24
## 2486 2021-02-13 South West 25
## 2487 2021-02-14 South West 15
## 2488 2021-02-15 South West 18
## 2489 2021-02-16 South West 10
## 2490 2021-02-17 South West 15
## 2491 2021-02-18 South West 9
## 2492 2021-02-19 South West 21.5 Completion date
We extract the completion date from the NHS Pathways file timestamp:
The completion date of the NHS Pathways data is Thursday 18 Feb 2021.
1.6 Auxiliary functions
These are functions which will be used further in the analyses.
Function to estimate the generalised R-squared as the proportion of deviance explained by a given model:
## Function to calculate R2 for Poisson model
## not adjusted for model complexity but all models have the same DF here
Rsq <- function(x) {
1 - (x$deviance / x$null.deviance)
}Function to extract growth rates per region as well as halving times, and the associated 95% confidence intervals:
## function to extract the coefficients, find the level of the intercept,
## reconstruct the values of r, get confidence intervals
get_r <- function(model) {
## extract coefficients and conf int
out <- data.frame(r = coef(model)) %>%
rownames_to_column("var") %>%
cbind(confint(model)) %>%
filter(!grepl("day_of_week", var)) %>%
filter(grepl("day", var)) %>%
rename(lower_95 = "2.5 %",
upper_95 = "97.5 %") %>%
mutate(var = sub("day:", "", var))
## reconstruct values: intercept + region-coefficient
for (i in 2:nrow(out)) {
out[i, -1] <- out[1, -1] + out[i, -1]
}
## find the name of the intercept, restore regions names
out <- out %>%
mutate(nhs_region = model$xlevels$nhs_region) %>%
select(nhs_region, everything(), -var)
## find halving times
halving <- log(0.5) / out[,-1] %>%
rename(halving_t = r,
halving_t_lower_95 = lower_95,
halving_t_upper_95 = upper_95)
## set halving times with exclusion intervals to NA
no_halving <- out$lower_95 < 0 & out$upper_95 > 0
halving[no_halving, ] <- NA_real_
## return all data
cbind(out, halving)
}Functions used in the correlation analysis between NHS Pathways reports and deaths:
## Function to calculate Pearson's correlation between deaths and lagged
## reports. Note that `pearson` can be replaced with `spearman` for rank
## correlation.
getcor <- function(x, ndx) {
return(cor(x$deaths[ndx],
x$note_lag[ndx],
use = "complete.obs",
method = "pearson"))
}
## Catch if sample size throws an error
getcor2 <- possibly(getcor, otherwise = NA)
getboot <- function(x) {
result <- boot::boot.ci(boot::boot(x, getcor2, R = 1000),
type = "bca")
return(data.frame(n = sum(!is.na(x$note_lag) & !is.na(x$deaths)),
r = result$t0,
r_low = result$bca[4],
r_hi = result$bca[5]))
}Function to classify the day of the week into weekend, Monday, and the rest:
## Fn to add day of week
day_of_week <- function(df) {
df %>%
dplyr::mutate(day_of_week = lubridate::wday(date, label = TRUE)) %>%
dplyr::mutate(day_of_week = dplyr::case_when(
day_of_week %in% c("Sat", "Sun") ~ "weekend",
day_of_week %in% c("Mon") ~ "monday",
!(day_of_week %in% c("Sat", "Sun", "Mon")) ~ "rest_of_week"
) %>%
factor(levels = c("rest_of_week", "monday", "weekend")))
}Custom color palettes, color scales, and vectors of colors:
2 Temporal trends in NHS Pathways reports
2.1 Outline
We look for temporal patterns in COVID-19 related 111/999 calls and 111 online reports. Analyses are broken down by NHS region. We also look for estimates of recent growth rate and associated doubling / halving time.
2.2 Reports by region over time
tab_date_region_all <- x %>%
filter(!is.na(nhs_region)) %>%
group_by(date, nhs_region) %>%
summarise(n = sum(count))
dth %>%
mutate(trusted = case_when(date_report < max(dth$date_report)-delay_max ~ "Y",
date_report >= max(dth$date_report)-delay_max ~ "N"),
value = "Deaths",
vline = max(dth$date_report)-delay_max-1,
lab = "Truncated for reporting delay",
lab_pos_x = vline + 10,
lab_pos_y = 150,
lab_col = "darkgrey") %>%
rename(date = date_report,
n = deaths) %>%
bind_rows(
mutate(tab_date_region_all, value = "Reports",
trusted = "Y",
vline = as.Date("2020-03-23"),
lab = "Start of UK lockdown",
lab_pos_x = vline - 8,
lab_pos_y = 30200,
lab_col = "black")
) %>%
mutate(value = factor(value, levels = c("Reports","Deaths"))) -> dths_reports
plot_dth_report <-
ggplot(dths_reports, aes(date, n, colour = nhs_region)) +
# Add main points and lines, coloured by region and fade out deaths for excluded period
geom_point(aes(alpha = trusted)) +
geom_line(alpha = 0.2) +
geom_smooth(method = "loess", span = .5, color = "black") +
scale_colour_manual("", values = pal) +
scale_alpha_manual(values = c(0.3,1)) +
guides(alpha = F) +
# Add vertical markers for important dates with labels - different for each facet
ggnewscale::new_scale_colour() +
geom_vline(aes(xintercept = vline, col = value), lty = "solid") +
geom_text(aes(x = lab_pos_x, y = lab_pos_y, label = lab, col = value), size = 3) +
scale_colour_manual("",values = c("black","darkgrey"), guide = F) +
# Facet by deaths and reports
facet_grid(rows = vars(value), scales = "free_y", switch = "y") +
# Other formatting
theme_bw() +
scale_weeks +
theme(legend.position = "bottom",strip.placement = "outside") +
rotate_x +
labs(x = NULL,
y = NULL)
plot_dth_report
2.3 Reports by region by age over time
We plot the number of 111/999 calls and 111 online reports by age, and the proportion of 111/999 calls and 111 online reports by age. In the second graph, the vertical lines indicate the proportion of individuals residing in the corresponding NHS region who belong to the corresponding age group.
tab_date_region_age_all <- x %>%
filter(!is.na(nhs_region),
age != "missing") %>%
group_by(date, nhs_region, age) %>%
summarise(n = sum(count))
tab_date_region_age_all %>%
ggplot(aes(x = date, y = n, fill = age)) +
geom_col(position = "stack") +
scale_fill_manual(values = age.pal) +
theme_bw() +
scale_weeks +
theme(legend.position = "bottom",
axis.text.x = element_text(angle = 90, hjust = 1)) +
guides(fill = guide_legend(title = "Age", ncol = 3)) +
labs(x = NULL,
y = "Total daily reports by age") +
facet_wrap(~ nhs_region, ncol = 4)
tab_date_region_age_all <- tab_date_region_age_all %>%
group_by(date, nhs_region) %>%
summarise(tot = sum(n)) %>%
left_join(tab_date_region_age_all, by = c("date", "nhs_region")) %>%
mutate(prop_n = n/tot)
tab_date_region_age_all %>%
ggplot(aes(x = date, y = prop_n, color = age)) +
scale_color_manual(values = age.pal) +
geom_line() +
geom_point() +
geom_hline(data = nhs_region_pop, aes(yintercept = value, color = variable)) +
theme_bw() +
scale_weeks +
theme(legend.position = "bottom",
axis.text.x = element_text(angle = 90, hjust = 1)) +
guides(color = guide_legend(title = "Age", ncol = 3)) +
labs(x = NULL,
y = "Proportion of daily reports by age") +
facet_wrap(~ nhs_region, ncol = 4)
2.4 Moving window model
We fit quasi-Poisson GLMs for 14-day windows to get growth rates over time.
## set moving time window (1/2/3 weeks)
w <- 14
# create empty df
r_all_sliding <- NULL
## make data for model
x_model_all_moving <- x %>%
filter(!is.na(nhs_region)) %>%
group_by(date, nhs_region) %>%
summarise(n = sum(count))
unique_dates <- unique(x_model_all_moving$date)
for (i in 1:(length(unique_dates) - w)) {
date_i <- unique_dates[i]
date_i_max <- date_i + w
model_data <- x_model_all_moving %>%
filter(date >= date_i & date < date_i_max) %>%
mutate(day = as.integer(date - date_i)) %>%
day_of_week()
mod <- glm(n ~ day * nhs_region + day_of_week,
data = model_data,
family = 'quasipoisson')
# get growth rate
r <- get_r(mod)
r$w_min <- date_i
r$w_max <- date_i_max
# combine all estimates
r_all_sliding <- bind_rows(r_all_sliding, r)
}
#serial interval distribution
SI_param = epitrix::gamma_mucv2shapescale(4.7, 2.9/4.7)
SI_distribution <- distcrete::distcrete("gamma", interval = 1,
shape = SI_param$shape,
scale = SI_param$scale,
w = 0.5)
#convert growth rates r to R0
r_all_sliding <- r_all_sliding %>%
mutate(R = epitrix::r2R0(r, SI_distribution),
R_lower_95 = epitrix::r2R0(lower_95, SI_distribution),
R_upper_95 = epitrix::r2R0(upper_95, SI_distribution))We examine the evolution of the growth rate by region over time.
# plot
plot_growth <-
r_all_sliding %>%
ggplot(aes(x = w_max, y = r)) +
geom_ribbon(aes(ymin = lower_95, ymax = upper_95, fill = nhs_region), alpha = 0.1) +
geom_line(aes(colour = nhs_region)) +
geom_point(aes(colour = nhs_region)) +
geom_hline(yintercept = 0, linetype = "dashed") +
theme_bw() +
scale_weeks +
theme(legend.position = "bottom",
plot.margin = margin(0.5,1,0.5,0.5, "cm")) +
guides(colour = guide_legend(title = "", override.aes = list(fill = NA)), fill = FALSE) +
labs(x = "",
y = "Estimated daily growth rate (r)") +
scale_colour_manual(values = pal)From the growth rate, we derive R and examine its value through time.
# plot
plot_R <-
r_all_sliding %>%
ggplot(aes(x = w_max, y = R)) +
geom_ribbon(aes(ymin = R_lower_95, ymax = R_upper_95, fill = nhs_region), alpha = 0.1) +
geom_line(aes(colour = nhs_region)) +
geom_point(aes(colour = nhs_region)) +
geom_hline(yintercept = 1, linetype = "dashed") +
theme_bw() +
scale_weeks +
theme(legend.position = "bottom",
plot.margin = margin(0.5,1,0.5,0.5, "cm")) +
guides(color = guide_legend(title = "", override.aes = list(fill = NA)), fill = FALSE) +
labs(x = "",
y = "Estimated effective reproduction\nnumber (Re)") +
scale_colour_manual(values = pal)
R <- r_all_sliding %>%
mutate(lower_95 = R_lower_95,
upper_95 = R_upper_95,
value = R,
measure = "R",
reference = 1)
r_R <- r_all_sliding %>%
mutate(measure = "r",
value = r,
reference = 0) %>%
bind_rows(R)
r_R %>%
ggplot(aes(x = w_max, y = value)) +
geom_ribbon(aes(ymin = lower_95, ymax = upper_95, fill = nhs_region), alpha = 0.1) +
geom_line(aes(colour = nhs_region)) +
geom_point(aes(colour = nhs_region)) +
geom_hline(aes(yintercept = reference), linetype = "dashed") +
theme_bw() +
scale_weeks +
rotate_x +
theme(legend.position = "bottom",
plot.margin = margin(0.5,1,0,0, "cm"),
strip.background = element_blank(),
# strip.text.x = element_blank(),
strip.placement = "outside"
) +
guides(color = guide_legend(title = "",
override.aes = list(fill = NA)),
fill = FALSE) +
labs(x = "", y = "") +
scale_colour_manual(values = pal) +
facet_grid(rows = vars(measure),
scales = "free_y",
switch = "y",
labeller = as_labeller(c(r = "Daily growth rate (r)",
R = "Effective reproduction\nnumber (Re)")))
2.5 Moving window model - stratified by age
We repeat the above analysis, where we fit quasi-Poisson GLMs for 14-day windows to get growth rates over time, but apply this to each age group separately (0-18, 19-69, 70-120 years old).
We first run the analysis for 0-18 years old.
## set moving time window (2 weeks)
w <- 14
# create empty df
r_all_sliding_0_18 <- NULL
## make data for model
x_model_all_moving_0_18 <- x %>%
filter(!is.na(nhs_region),
age == "0-18") %>%
group_by(date, nhs_region) %>%
summarise(n = sum(count))
unique_dates <- unique(x_model_all_moving_0_18$date)
for (i in 1:(length(unique_dates) - w)) {
date_i <- unique_dates[i]
date_i_max <- date_i + w
model_data <- x_model_all_moving_0_18 %>%
filter(date >= date_i & date < date_i_max) %>%
mutate(day = as.integer(date - date_i)) %>%
day_of_week()
mod <- glm(n ~ day * nhs_region + day_of_week,
data = model_data,
family = 'quasipoisson')
# get growth rate
r <- get_r(mod)
r$w_min <- date_i
r$w_max <- date_i_max
# combine all estimates
r_all_sliding_0_18 <- bind_rows(r_all_sliding_0_18, r)
}
#serial interval distribution
SI_param = epitrix::gamma_mucv2shapescale(4.7, 2.9/4.7)
SI_distribution <- distcrete::distcrete("gamma", interval = 1,
shape = SI_param$shape,
scale = SI_param$scale, w = 0.5)
#convert growth rates r to R0
r_all_sliding_0_18 <- r_all_sliding_0_18 %>%
mutate(R = epitrix::r2R0(r, SI_distribution),
R_lower_95 = epitrix::r2R0(lower_95, SI_distribution),
R_upper_95 = epitrix::r2R0(upper_95, SI_distribution))# plot
plot_growth <-
r_all_sliding_0_18 %>%
ggplot(aes(x = w_max, y = r)) +
geom_ribbon(aes(ymin = lower_95, ymax = upper_95, fill = nhs_region), alpha = 0.1) +
geom_line(aes(colour = nhs_region)) +
geom_point(aes(colour = nhs_region)) +
geom_hline(yintercept = 0, linetype = "dashed") +
theme_bw() +
scale_weeks +
theme(legend.position = "bottom",
plot.margin = margin(0.5,1,0.5,0.5, "cm")) +
guides(colour = guide_legend(title = "",override.aes = list(fill = NA)), fill = FALSE) +
labs(x = "",
y = "Estimated daily growth rate (r)"
) +
scale_colour_manual(values = pal)# plot
plot_R <-
r_all_sliding_0_18 %>%
ggplot(aes(x = w_max, y = R)) +
geom_ribbon(aes(ymin = R_lower_95, ymax = R_upper_95, fill = nhs_region), alpha = 0.1) +
geom_line(aes(colour = nhs_region)) +
geom_point(aes(colour = nhs_region)) +
geom_hline(yintercept = 1, linetype = "dashed") +
theme_bw() +
scale_weeks +
theme(legend.position = "bottom",
plot.margin = margin(0.5,1,0.5,0.5, "cm")) +
guides(color = guide_legend(title = "", override.aes = list(fill = NA)), fill = FALSE) +
labs(x = "",
y = "Estimated effective reproduction\nnumber (Re)"
) +
scale_colour_manual(values = pal)
R <- r_all_sliding_0_18 %>%
mutate(lower_95 = R_lower_95,
upper_95 = R_upper_95,
value = R,
measure = "R",
reference = 1)
r_R <- r_all_sliding_0_18 %>%
mutate(measure = "r",
value = r,
reference = 0) %>%
bind_rows(R)
fig2_3_0_18 <- r_R %>%
ggplot(aes(x = w_max, y = value)) +
geom_ribbon(aes(ymin = lower_95, ymax = upper_95, fill = nhs_region), alpha = 0.1) +
geom_line(aes(colour = nhs_region)) +
geom_point(aes(colour = nhs_region)) +
geom_hline(aes(yintercept = reference), linetype = "dashed") +
theme_bw() +
scale_weeks +
theme(legend.position = "bottom",
plot.margin = margin(0.5,1,0,0, "cm"),
strip.background = element_blank(),
strip.placement = "outside"
) +
guides(color = guide_legend(title = "", override.aes = list(fill = NA)), fill = FALSE) +
labs(x = "", y = "") +
scale_colour_manual(values = pal) +
facet_grid(rows = vars(measure),
scales = "free_y",
switch = "y",
labeller = as_labeller(c(r = "Daily growth rate (r)",
R = "Effective reproduction\nnumber (Re)")))Then, we run the analysis for 19-69 years old.
## set moving time window (2 weeks)
w <- 14
# create empty df
r_all_sliding_19_69 <- NULL
## make data for model
x_model_all_moving_19_69 <- x %>%
filter(!is.na(nhs_region),
age == "19-69") %>%
group_by(date, nhs_region) %>%
summarise(n = sum(count))
unique_dates <- unique(x_model_all_moving_19_69$date)
for (i in 1:(length(unique_dates) - w)) {
date_i <- unique_dates[i]
date_i_max <- date_i + w
model_data <- x_model_all_moving_19_69 %>%
filter(date >= date_i & date < date_i_max) %>%
mutate(day = as.integer(date - date_i)) %>%
day_of_week()
mod <- glm(n ~ day * nhs_region + day_of_week,
data = model_data,
family = 'quasipoisson')
# get growth rate
r <- get_r(mod)
r$w_min <- date_i
r$w_max <- date_i_max
# combine all estimates
r_all_sliding_19_69 <- bind_rows(r_all_sliding_19_69, r)
}
#serial interval distribution
SI_param = epitrix::gamma_mucv2shapescale(4.7, 2.9/4.7)
SI_distribution <- distcrete::distcrete("gamma", interval = 1,
shape = SI_param$shape,
scale = SI_param$scale, w = 0.5)
#convert growth rates r to R0
r_all_sliding_19_69 <- r_all_sliding_19_69 %>%
mutate(R = epitrix::r2R0(r, SI_distribution),
R_lower_95 = epitrix::r2R0(lower_95, SI_distribution),
R_upper_95 = epitrix::r2R0(upper_95, SI_distribution))# plot
plot_growth <-
r_all_sliding_19_69 %>%
ggplot(aes(x = w_max, y = r)) +
geom_ribbon(aes(ymin = lower_95, ymax = upper_95, fill = nhs_region), alpha = 0.1) +
geom_line(aes(colour = nhs_region)) +
geom_point(aes(colour = nhs_region)) +
geom_hline(yintercept = 0, linetype = "dashed") +
theme_bw() +
scale_weeks +
theme(legend.position = "bottom",
plot.margin = margin(0.5,1,0.5,0.5, "cm")) +
guides(colour = guide_legend(title = "", override.aes = list(fill = NA)), fill = FALSE) +
labs(x = "",
y = "Estimated daily growth rate (r)") +
scale_colour_manual(values = pal)# plot
plot_R <-
r_all_sliding_19_69 %>%
ggplot(aes(x = w_max, y = R)) +
geom_ribbon(aes(ymin = R_lower_95, ymax = R_upper_95, fill = nhs_region), alpha = 0.1) +
geom_line(aes(colour = nhs_region)) +
geom_point(aes(colour = nhs_region)) +
geom_hline(yintercept = 1, linetype = "dashed") +
theme_bw() +
scale_weeks +
theme(legend.position = "bottom",
plot.margin = margin(0.5,1,0.5,0.5, "cm")) +
guides(color = guide_legend(title = "", override.aes = list(fill = NA)), fill = FALSE) +
labs(x = "",
y = "Estimated effective reproduction\nnumber (Re)"
) +
scale_colour_manual(values = pal)
R <- r_all_sliding_19_69 %>%
mutate(lower_95 = R_lower_95,
upper_95 = R_upper_95,
value = R,
measure = "R",
reference = 1)
r_R <- r_all_sliding_19_69 %>%
mutate(measure = "r",
value = r,
reference = 0) %>%
bind_rows(R)
fig2_3_19_69 <- r_R %>%
ggplot(aes(x = w_max, y = value)) +
geom_ribbon(aes(ymin = lower_95, ymax = upper_95, fill = nhs_region), alpha = 0.1) +
geom_line(aes(colour = nhs_region)) +
geom_point(aes(colour = nhs_region)) +
geom_hline(aes(yintercept = reference), linetype = "dashed") +
theme_bw() +
scale_weeks +
theme(legend.position = "bottom",
plot.margin = margin(0.5,1,0,0, "cm"),
strip.background = element_blank(),
strip.placement = "outside"
) +
guides(color = guide_legend(title = "", override.aes = list(fill = NA)), fill = FALSE) +
labs(x = "", y = "") +
scale_colour_manual(values = pal) +
facet_grid(rows = vars(measure),
scales = "free_y",
switch = "y",
labeller = as_labeller(c(r = "Daily growth rate (r)",
R = "Effective reproduction\nnumber (Re)")))Finally, we run the analysis for 70-120 years old.
## set moving time window (2 weeks)
w <- 14
# create empty df
r_all_sliding_70_120 <- NULL
## make data for model
x_model_all_moving_70_120 <- x %>%
filter(!is.na(nhs_region),
age == "70-120") %>%
group_by(date, nhs_region) %>%
summarise(n = sum(count))
unique_dates <- unique(x_model_all_moving_70_120$date)
for (i in 1:(length(unique_dates) - w)) {
date_i <- unique_dates[i]
date_i_max <- date_i + w
model_data <- x_model_all_moving_70_120 %>%
filter(date >= date_i & date < date_i_max) %>%
mutate(day = as.integer(date - date_i)) %>%
day_of_week()
mod <- glm(n ~ day * nhs_region + day_of_week,
data = model_data,
family = 'quasipoisson')
# get growth rate
r <- get_r(mod)
r$w_min <- date_i
r$w_max <- date_i_max
# combine all estimates
r_all_sliding_70_120 <- bind_rows(r_all_sliding_70_120, r)
}
#serial interval distribution
SI_param = epitrix::gamma_mucv2shapescale(4.7, 2.9/4.7)
SI_distribution <- distcrete::distcrete("gamma", interval = 1,
shape = SI_param$shape,
scale = SI_param$scale, w = 0.5)
#convert growth rates r to R0
r_all_sliding_70_120 <- r_all_sliding_70_120 %>%
mutate(R = epitrix::r2R0(r, SI_distribution),
R_lower_95 = epitrix::r2R0(lower_95, SI_distribution),
R_upper_95 = epitrix::r2R0(upper_95, SI_distribution))# plot
plot_growth <-
r_all_sliding_70_120 %>%
ggplot(aes(x = w_max, y = r)) +
geom_ribbon(aes(ymin = lower_95, ymax = upper_95, fill = nhs_region), alpha = 0.1) +
geom_line(aes(colour = nhs_region)) +
geom_point(aes(colour = nhs_region)) +
geom_hline(yintercept = 0, linetype = "dashed") +
theme_bw() +
scale_weeks +
theme(legend.position = "bottom",
plot.margin = margin(0.5,1,0.5,0.5, "cm")) +
guides(colour = guide_legend(title = "",override.aes = list(fill = NA)), fill = FALSE) +
labs(x = "",
y = "Estimated daily growth rate (r)"
) +
scale_colour_manual(values = pal)# plot
plot_R <-
r_all_sliding_70_120 %>%
ggplot(aes(x = w_max, y = R)) +
geom_ribbon(aes(ymin = R_lower_95, ymax = R_upper_95, fill = nhs_region), alpha = 0.1) +
geom_line(aes(colour = nhs_region)) +
geom_point(aes(colour = nhs_region)) +
geom_hline(yintercept = 1, linetype = "dashed") +
theme_bw() +
scale_weeks +
theme(legend.position = "bottom",
plot.margin = margin(0.5,1,0.5,0.5, "cm")) +
guides(color = guide_legend(title = "", override.aes = list(fill = NA)), fill = FALSE) +
labs(x = "",
y = "Estimated effective reproduction\nnumber (Re)") +
scale_colour_manual(values = pal)
R <- r_all_sliding_70_120 %>%
mutate(lower_95 = R_lower_95,
upper_95 = R_upper_95,
value = R,
measure = "R",
reference = 1)
r_R <- r_all_sliding_70_120 %>%
mutate(measure = "r",
value = r,
reference = 0) %>%
bind_rows(R)
fig2_3_70_120 <- r_R %>%
ggplot(aes(x = w_max, y = value)) +
geom_ribbon(aes(ymin = lower_95, ymax = upper_95, fill = nhs_region), alpha = 0.1) +
geom_line(aes(colour = nhs_region)) +
geom_point(aes(colour = nhs_region)) +
geom_hline(aes(yintercept = reference), linetype = "dashed") +
theme_bw() +
scale_weeks +
theme(legend.position = "bottom",
plot.margin = margin(0.5,1,0,0, "cm"),
strip.background = element_blank(),
strip.placement = "outside"
) +
guides(color = guide_legend(title = "", override.aes = list(fill = NA)), fill = FALSE) +
labs(x = "", y = "") +
scale_colour_manual(values = pal) +
facet_grid(rows = vars(measure),
scales = "free_y",
switch = "y",
labeller = as_labeller(c(r = "Daily growth rate (r)",
R = "Effective reproduction\nnumber (Re)"))) We combine the estimated growth rates and effective reproduction numbers into a single figure.
ggpubr::ggarrange(fig2_3_0_18,
fig2_3_19_69,
fig2_3_70_120,
nrow = 3,
labels = "AUTO",
common.legend = TRUE,
legend = "bottom",
align = "hv") 
3 Comparison with deaths time series
3.1 Outline
We want to explore the correlation between NHS Pathways reports and deaths, and assess the potential for reports to be used as an early warning system for disease resurgence.
Death data are publically available. We truncate the time series to avoid bias from reporting delay - we assume a conservative delay of three weeks.
3.2 Lagged correlation
We calculate Pearson’s correlation coefficient between deaths and NHS Pathways notifications using different lags. Confidence intervals are obtained using bootstrap. Note that results were also confirmed using Spearman’s rank correlation.
First we join the NHS Pathways and death data, and aggregate over all England:
## truncate death data for reporting delay
trunc_date <- max(dth$date_report) - delay_max
dth_trunc <- dth %>%
rename(date = date_report) %>%
filter(date <= trunc_date)
## join with notification data
all_data <- x %>%
filter(!is.na(nhs_region)) %>%
group_by(date, nhs_region) %>%
summarise(count = sum(count, na.rm = T)) %>%
ungroup %>%
inner_join(dth_trunc,
by = c("date","nhs_region"))
all_tot <- all_data %>%
group_by(date) %>%
summarise(count = sum(count, na.rm = TRUE),
deaths = sum(deaths, na.rm = TRUE)) We calculate correlation with lagged NHS Pathways reports from 0 to 30 days behind deaths:
## Calculate all correlations + bootstrap CIs
lag_cor <- data.frame()
for (i in 0:30) {
## lag reports
summary <- all_tot %>%
mutate(note_lag = lag(count, i)) %>%
## calculate rank correlation and bootstrap CI
getboot(.) %>%
mutate(lag = i)
lag_cor <- bind_rows(lag_cor, summary)
}
cor_vs_lag <- ggplot(lag_cor, aes(lag, r)) +
theme_bw() +
geom_ribbon(aes(ymin = r_low, ymax = r_hi), alpha = 0.2) +
geom_hline(yintercept = 0, lty = "longdash") +
geom_point() +
geom_line() +
labs(x = "Lag between NHS pathways and death data (days)",
y = "Pearson's correlation") +
large_txt
cor_vs_lag
This analysis suggests that the best lag is 15 days. We then compare and plot the number of deaths reported against the number of NHS Pathways reports lagged by 15 days.
all_tot <- all_tot %>%
rename(date_death = date) %>%
mutate(note_lag = lag(count, lag_cor$lag[l_opt]),
note_lag_c = (note_lag - mean(note_lag, na.rm = T)),
date_note = lag(date_death,16))
lag_mod <- glm(deaths ~ note_lag, data = all_tot, family = "quasipoisson")
summary(lag_mod)
##
## Call:
## glm(formula = deaths ~ note_lag, family = "quasipoisson", data = all_tot)
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -18.240 -15.649 -5.721 6.722 33.960
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 5.129e+00 7.072e-02 72.525 <2e-16 ***
## note_lag 1.216e-05 1.263e-06 9.625 <2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## (Dispersion parameter for quasipoisson family taken to be 224.0943)
##
## Null deviance: 77252 on 302 degrees of freedom
## Residual deviance: 62043 on 301 degrees of freedom
## (15 observations deleted due to missingness)
## AIC: NA
##
## Number of Fisher Scoring iterations: 5
exp(coefficients(lag_mod))
## (Intercept) note_lag
## 168.833374 1.000012
exp(confint(lag_mod))
## 2.5 % 97.5 %
## (Intercept) 146.58033 193.429132
## note_lag 1.00001 1.000015
Rsq(lag_mod)
## [1] 0.1968705
mod_fit <- as.data.frame(predict(lag_mod, type = "link", se.fit = TRUE)[1:2])
all_tot_pred <-
all_tot %>%
filter(!is.na(note_lag)) %>%
mutate(pred = mod_fit$fit,
pred.se = mod_fit$se.fit,
low = exp(pred - 1.96*pred.se),
hi = exp(pred + 1.96*pred.se))
glm_fit <- all_tot_pred %>%
filter(!is.na(note_lag)) %>%
ggplot(aes(x = note_lag, y = deaths)) +
geom_point() +
geom_line(aes(y = exp(pred))) +
geom_ribbon(aes(ymin = low, ymax = hi), alpha = 0.3, col = "grey") +
theme_bw() +
labs(y = "Daily number of\ndeaths reported",
x = "Daily number of NHS Pathways reports") +
large_txt
glm_fit
4 Supplementary figures
4.1 Serial interval distribution
This is a comparison of gamma versus lognormal distribution for the serial interval used to convert r to R in our analysis. Both distributions are parameterised with mean 4.7 and standard deviation 2.9.
SI_param <- epitrix::gamma_mucv2shapescale(4.7, 2.9/4.7)
SI_distribution <- distcrete::distcrete("gamma", interval = 1,
shape = SI_param$shape,
scale = SI_param$scale, w = 0.5)
SI_distribution2 <- distcrete::distcrete("lnorm", interval = 1,
meanlog = log(4.7),
sdlog = log(2.9), w = 0.5)
SI_dist1 <- data.frame(x = SI_distribution$r(1e5))
SI_dist1 <- count(SI_dist1, x) %>%
ggplot() +
geom_col(aes(x = x, y = n)) +
labs(x = "Serial interval (days)", y = "Frequency") +
scale_x_continuous(breaks = seq(0, 30, 5)) +
theme_bw()
SI_dist2 <- data.frame(x = SI_distribution2$r(1e5))
SI_dist2 <- count(SI_dist2, x) %>%
ggplot() +
geom_col(aes(x = x, y = n)) +
labs(x = "Serial interval (days)", y = "Frequency") +
scale_x_continuous(breaks = seq(0, 200, 20), limits = c(0, 200)) +
theme_bw()
ggpubr::ggarrange(SI_dist1,
SI_dist2,
nrow = 1,
labels = "AUTO") 
4.2 Sensitivity analysis - 7 or 21 days moving window
We reproduce the window analysis with either a 7 or 21 days window for sensitivity purposes.
First with the 7 days window:
## set moving time window (1/2/3 weeks)
w <- 7
# create empty df
r_all_sliding_7days <- NULL
## make data for model
x_model_all_moving <- x %>%
filter(!is.na(nhs_region)) %>%
group_by(date, nhs_region) %>%
summarise(n = sum(count))
unique_dates <- unique(x_model_all_moving$date)
for (i in 1:(length(unique_dates) - w)) {
date_i <- unique_dates[i]
date_i_max <- date_i + w
model_data <- x_model_all_moving %>%
filter(date >= date_i & date < date_i_max) %>%
mutate(day = as.integer(date - date_i)) %>%
day_of_week()
mod <- glm(n ~ day * nhs_region + day_of_week,
data = model_data,
family = 'quasipoisson')
# get growth rate
r <- get_r(mod)
r$w_min <- date_i
r$w_max <- date_i_max
# combine all estimates
r_all_sliding_7days <- bind_rows(r_all_sliding_7days, r)
}
#serial interval distribution
SI_param = epitrix::gamma_mucv2shapescale(4.7, 2.9/4.7)
SI_distribution <- distcrete::distcrete("gamma", interval = 1,
shape = SI_param$shape,
scale = SI_param$scale,
w = 0.5)
#convert growth rates r to R0
r_all_sliding_7days <- r_all_sliding_7days %>%
mutate(R = epitrix::r2R0(r, SI_distribution),
R_lower_95 = epitrix::r2R0(lower_95, SI_distribution),
R_upper_95 = epitrix::r2R0(upper_95, SI_distribution))# plot
plot_growth <-
r_all_sliding_7days %>%
ggplot(aes(x = w_max, y = r)) +
geom_ribbon(aes(ymin = lower_95, ymax = upper_95, fill = nhs_region), alpha = 0.1) +
geom_line(aes(colour = nhs_region)) +
geom_point(aes(colour = nhs_region)) +
geom_hline(yintercept = 0, linetype = "dashed") +
theme_bw() +
scale_weeks +
theme(legend.position = "bottom",
plot.margin = margin(0.5,1,0.5,0.5, "cm")) +
guides(colour = guide_legend(title = "",override.aes = list(fill = NA)), fill = FALSE) +
labs(x = "",
y = "Estimated daily growth rate (r)") +
scale_colour_manual(values = pal)plot_R <- r_all_sliding_7days %>%
ggplot(aes(x = w_max, y = R)) +
geom_ribbon(aes(ymin = R_lower_95, ymax = R_upper_95, fill = nhs_region), alpha = 0.1) +
geom_line(aes(colour = nhs_region)) +
geom_point(aes(colour = nhs_region)) +
geom_hline(yintercept = 1, linetype = "dashed") +
theme_bw() +
scale_weeks +
theme(legend.position = "bottom",
plot.margin = margin(0.5,1,0.5,0.5, "cm")) +
guides(color = guide_legend(title = "", override.aes = list(fill = NA)), fill = FALSE) +
labs(x = "",
y = "Estimated effective reproduction\nnumber (Re)") +
scale_colour_manual(values = pal)
R <- r_all_sliding_7days %>%
mutate(lower_95 = R_lower_95,
upper_95 = R_upper_95,
value = R,
measure = "R",
reference = 1)
r_R <- r_all_sliding_7days %>%
mutate(measure = "r",
value = r,
reference = 0) %>%
bind_rows(R)
r_R_7 <- r_R %>%
ggplot(aes(x = w_max, y = value)) +
geom_ribbon(aes(ymin = lower_95, ymax = upper_95, fill = nhs_region), alpha = 0.1) +
geom_line(aes(colour = nhs_region)) +
geom_point(aes(colour = nhs_region)) +
geom_hline(aes(yintercept = reference), linetype = "dashed") +
theme_bw() +
scale_weeks +
theme(legend.position = "bottom",
plot.margin = margin(0.5,1,0,0, "cm"),
strip.background = element_blank(),
strip.placement = "outside"
) +
guides(color = guide_legend(title = "", override.aes = list(fill = NA)), fill = FALSE) +
labs(x = "", y = "") +
scale_colour_manual(values = pal) +
facet_grid(rows = vars(measure),
scales = "free_y",
switch = "y",
labeller = as_labeller(c(r = "Daily growth rate (r)",
R = "Effective reproduction\nnumber (Re)")))Then with the 21 days window:
## set moving time window (1/2/3 weeks)
w <- 21
# create empty df
r_all_sliding_21days <- NULL
## make data for model
x_model_all_moving <- x %>%
filter(!is.na(nhs_region)) %>%
group_by(date, nhs_region) %>%
summarise(n = sum(count))
unique_dates <- unique(x_model_all_moving$date)
for (i in 1:(length(unique_dates) - w)) {
date_i <- unique_dates[i]
date_i_max <- date_i + w
model_data <- x_model_all_moving %>%
filter(date >= date_i & date < date_i_max) %>%
mutate(day = as.integer(date - date_i)) %>%
day_of_week()
mod <- glm(n ~ day * nhs_region + day_of_week,
data = model_data,
family = 'quasipoisson')
# get growth rate
r <- get_r(mod)
r$w_min <- date_i
r$w_max <- date_i_max
# combine all estimates
r_all_sliding_21days <- bind_rows(r_all_sliding_21days, r)
}
#serial interval distribution
SI_param = epitrix::gamma_mucv2shapescale(4.7, 2.9/4.7)
SI_distribution <- distcrete::distcrete("gamma", interval = 1,
shape = SI_param$shape,
scale = SI_param$scale,
w = 0.5)
#convert growth rates r to R0
r_all_sliding_21days <- r_all_sliding_21days %>%
mutate(R = epitrix::r2R0(r, SI_distribution),
R_lower_95 = epitrix::r2R0(lower_95, SI_distribution),
R_upper_95 = epitrix::r2R0(upper_95, SI_distribution))# plot
plot_growth <-
r_all_sliding_21days %>%
ggplot(aes(x = w_max, y = r)) +
geom_ribbon(aes(ymin = lower_95, ymax = upper_95, fill = nhs_region), alpha = 0.1) +
geom_line(aes(colour = nhs_region)) +
geom_point(aes(colour = nhs_region)) +
geom_hline(yintercept = 0, linetype = "dashed") +
theme_bw() +
scale_weeks +
theme(legend.position = "bottom",
plot.margin = margin(0.5,1,0.5,0.5, "cm")) +
guides(colour = guide_legend(title = "",override.aes = list(fill = NA)), fill = FALSE) +
labs(x = "",
y = "Estimated daily growth rate (r)") +
scale_colour_manual(values = pal)# plot
plot_R <-
r_all_sliding_21days %>%
ggplot(aes(x = w_max, y = R)) +
geom_ribbon(aes(ymin = R_lower_95, ymax = R_upper_95, fill = nhs_region), alpha = 0.1) +
geom_line(aes(colour = nhs_region)) +
geom_point(aes(colour = nhs_region)) +
geom_hline(yintercept = 1, linetype = "dashed") +
theme_bw() +
scale_weeks +
theme(legend.position = "bottom",
plot.margin = margin(0.5,1,0.5,0.5, "cm")) +
guides(color = guide_legend(title = "", override.aes = list(fill = NA)), fill = FALSE) +
labs(x = "",
y = "Estimated effective reproduction\nnumber (Re)") +
scale_colour_manual(values = pal)
R <- r_all_sliding_21days %>%
mutate(lower_95 = R_lower_95,
upper_95 = R_upper_95,
value = R,
measure = "R",
reference = 1)
r_R <- r_all_sliding_21days %>%
mutate(measure = "r",
value = r,
reference = 0) %>%
bind_rows(R)
r_R_21 <- r_R %>%
ggplot(aes(x = w_max, y = value)) +
geom_ribbon(aes(ymin = lower_95, ymax = upper_95, fill = nhs_region), alpha = 0.1) +
geom_line(aes(colour = nhs_region)) +
geom_point(aes(colour = nhs_region)) +
geom_hline(aes(yintercept = reference), linetype = "dashed") +
theme_bw() +
scale_weeks +
theme(legend.position = "bottom",
plot.margin = margin(0.5,1,0,0, "cm"),
strip.background = element_blank(),
strip.placement = "outside"
) +
guides(color = guide_legend(title = "", override.aes = list(fill = NA)), fill = FALSE) +
labs(x = "", y = "") +
scale_colour_manual(values = pal) +
facet_grid(rows = vars(measure),
scales = "free_y",
switch = "y",
labeller = as_labeller(c(r = "Daily growth rate (r)",
R = "Effective reproduction\nnumber (Re)")))And we combine both outputs into a single plot:
ggpubr::ggarrange(r_R_7,
r_R_21,
nrow = 2,
labels = "AUTO",
common.legend = TRUE,
legend = "bottom") 
4.3 Correlation between NHS Pathways reports and deaths by NHS region
lag_cor_reg <- data.frame()
for (i in 0:30) {
summary <-
all_data %>%
group_by(nhs_region) %>%
mutate(note_lag = lag(count, i)) %>%
## calculate rank correlation and bootstrap CI for each region
group_modify(~getboot(.x)) %>%
mutate(lag = i)
lag_cor_reg <- bind_rows(lag_cor_reg, summary)
}
cor_vs_lag_reg <-
lag_cor_reg %>%
ggplot(aes(lag, r, col = nhs_region)) +
geom_hline(yintercept = 0, lty = "longdash") +
geom_ribbon(aes(ymin = r_low, ymax = r_hi, col = NULL, fill = nhs_region), alpha = 0.2) +
geom_point() +
geom_line() +
facet_wrap(~nhs_region) +
scale_color_manual(values = pal) +
scale_fill_manual(values = pal, guide = F) +
theme_bw() +
labs(x = "Lag between NHS pathways and death data (days)", y = "Pearson's correlation", col = "NHS region") +
theme(legend.position = "bottom") +
guides(color = guide_legend(override.aes = list(fill = NA)))
cor_vs_lag_reg
5 Export data
We save the tables created during our analysis:
if (!dir.exists("excel_tables")) {
dir.create("excel_tables")
}
## list all tables, and loop over export
tables_to_export <- c("r_all_sliding", "lag_cor")
for (e in tables_to_export) {
rio::export(get(e),
file.path("excel_tables",
paste0(e, ".xlsx")))
}
## also export result from regression on lagged data
rio::export(lag_mod, file.path("excel_tables", "lag_mod.rds"))6 System information
6.1 Outline
The following information documents the system on which the document was compiled.
6.2 System
This provides information on the operating system.
Sys.info()
## sysname
## "Darwin"
## release
## "19.6.0"
## version
## "Darwin Kernel Version 19.6.0: Tue Jan 12 22:13:05 PST 2021; root:xnu-6153.141.16~1/RELEASE_X86_64"
## nodename
## "Mac-1613902140031.local"
## machine
## "x86_64"
## login
## "root"
## user
## "runner"
## effective_user
## "runner"6.3 R environment
This provides information on the version of R used:
6.4 R packages
This provides information on the packages used:
sessionInfo()
## R version 4.0.4 (2021-02-15)
## Platform: x86_64-apple-darwin17.0 (64-bit)
## Running under: macOS Catalina 10.15.7
##
## Matrix products: default
## BLAS: /Library/Frameworks/R.framework/Versions/4.0/Resources/lib/libRblas.dylib
## LAPACK: /Library/Frameworks/R.framework/Versions/4.0/Resources/lib/libRlapack.dylib
##
## locale:
## [1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8
##
## attached base packages:
## [1] stats graphics grDevices utils datasets methods base
##
## other attached packages:
## [1] ggnewscale_0.4.5 ggpubr_0.4.0 lubridate_1.7.9.2
## [4] chngpt_2020.10-12 cyphr_1.1.0 DT_0.17
## [7] kableExtra_1.3.4 janitor_2.1.0 remotes_2.2.0
## [10] projections_0.5.2 earlyR_0.0.5 epitrix_0.2.2
## [13] distcrete_1.0.3 incidence_1.7.3 rio_0.5.16
## [16] reshape2_1.4.4 rvest_0.3.6 xml2_1.3.2
## [19] linelist_0.0.40.9000 forcats_0.5.1 stringr_1.4.0
## [22] dplyr_1.0.4 purrr_0.3.4 readr_1.4.0
## [25] tidyr_1.1.2 tibble_3.0.6 ggplot2_3.3.3
## [28] tidyverse_1.3.0 here_1.0.1 reportfactory_0.0.5
##
## loaded via a namespace (and not attached):
## [1] minqa_1.2.4 colorspace_2.0-0 selectr_0.4-2 ggsignif_0.6.0
## [5] ellipsis_0.3.1 rprojroot_2.0.2 snakecase_0.11.0 fs_1.5.0
## [9] rstudioapi_0.13 farver_2.0.3 fansi_0.4.2 splines_4.0.4
## [13] knitr_1.31 jsonlite_1.7.2 nloptr_1.2.2.2 broom_0.7.5
## [17] dbplyr_2.1.0 compiler_4.0.4 httr_1.4.2 backports_1.2.1
## [21] assertthat_0.2.1 Matrix_1.3-2 cli_2.3.0 htmltools_0.5.1.1
## [25] tools_4.0.4 gtable_0.3.0 glue_1.4.2 Rcpp_1.0.6
## [29] carData_3.0-4 cellranger_1.1.0 vctrs_0.3.6 svglite_2.0.0
## [33] nlme_3.1-152 matchmaker_0.1.1 crosstalk_1.1.1 xfun_0.21
## [37] ps_1.5.0 openxlsx_4.2.3 lme4_1.1-26 lifecycle_1.0.0
## [41] statmod_1.4.35 rstatix_0.7.0 MASS_7.3-53 scales_1.1.1
## [45] hms_1.0.0 parallel_4.0.4 sodium_1.1 yaml_2.2.1
## [49] curl_4.3 gridExtra_2.3 stringi_1.5.3 highr_0.8
## [53] kyotil_2020.10-12 boot_1.3-26 zip_2.1.1 rlang_0.4.10
## [57] pkgconfig_2.0.3 systemfonts_1.0.1 evaluate_0.14 lattice_0.20-41
## [61] labeling_0.4.2 htmlwidgets_1.5.3 cowplot_1.1.1 tidyselect_1.1.0
## [65] plyr_1.8.6 magrittr_2.0.1 R6_2.5.0 generics_0.1.0
## [69] DBI_1.1.1 mgcv_1.8-33 pillar_1.4.7 haven_2.3.1
## [73] foreign_0.8-81 withr_2.4.1 survival_3.2-7 abind_1.4-5
## [77] modelr_0.1.8 crayon_1.4.1 car_3.0-10 utf8_1.1.4
## [81] rmarkdown_2.7 viridis_0.5.1 grid_4.0.4 readxl_1.3.1
## [85] data.table_1.14.0 reprex_1.0.0 digest_0.6.27 webshot_0.5.2
## [89] munsell_0.5.0 viridisLite_0.3.0